Your tasks will include:

• Designing scalable KI architectures: developing high-performance architectures and integrating ML and GenAI models into customer environments (e.g., SAP, CRM, Microservices)
• Implementing pipelines and workflows: building scalable data and AI architectures, integrating them into existing pipelines, and developing XOps solutions
• Backend services and system integration: developing high-performance services to integrate models into productive workflows and ensuring smooth transitions between training, deployment, and application
• Deployment, monitoring, and optimization: implementing prototypes and MVPs in cloud environments, optimizing performance, and ensuring scalability and security
• Identifying use cases: analyzing business processes, recognizing potential for GenAI, and deriving technical solutions
• Project and stakeholder management: moderating workshops, closely coordinating with interdisciplinary teams, international project partners, and customers

To be well-prepared for your path, you should have the following qualifications:

• Completed studies in computer science, software engineering, data science, or a comparable field with at least 4 years of professional experience, ideally in consulting and (Gen)AI
• Passion for AI and Generative AI, scalable systems, cloud technologies, and building high-performance AI infrastructure
• Expertise in Python, ML, LLMs, RAG, cloud environments (Azure, AWS, GCP), Docker, Kubernetes, REST APIs, CI/CD
• Knowledge in software architecture, cloud-native design, MLOps, and AI security
• Your work style is characterized by self-responsibility, goal orientation, teamwork, and hands-on mentality

Before departure:

• Start date: after agreement - always at the beginning of a month
• Working hours: full-time (40 hours) and/or part-time possible; 30 vacation days
• Employment relationship: unlimited
• Field: consulting
• Language: secure German and English
• Flexibility and travel readiness
• Other: valid work permit; if necessary, we can apply for a work permit within our recruitment process. The procedure takes time and affects the start date

At MHP, you grow continuously in an innovative and supportive environment. This makes us the perfect sparring partner for your career. For both professional input and networking. We offer you:

• Appreciation. We support and appreciate colleagues as they are and celebrate our successes together
• We are always happy about creativity and new impulses
• Flexibility. Time-wise and location-wise - according to the project at home, in the office, or at the customer
• You have the opportunity to grow with us in tasks, knowledge, and responsibility

To apply, please submit your application as soon as possible. Simply online through our Job Locator. There, you can send your application documents, such as resume, certificates, and possibly project lists, in just a few clicks to us. A cover letter is not required.

By the way: If your application reaches us, our recruiting team checks across departments whether there is a suitable position for you. Irrespective of current job postings, we try to find the right job for you at MHP.

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Your tasks will include:

• Data acquisition, cleaning, and feature engineering: extracting, transforming, and cleaning data from various sources, developing new features for ML and GenAI models, and agent systems
• Explorative data analysis and modeling: conducting analyses, developing and evaluating ML/GenAI prototypes, concepts for self-learning systems, and human-in-the-loop approaches
• Prototyping and integration: creating prototypes in Python, integrating models into systems or cloud environments, and implementing AI solutions based on LLM
• Identification of use cases: analyzing business processes, recognizing opportunities for GenAI, and deriving technical solutions, integrating them into existing system and process landscapes
• Project and stakeholder management: moderating workshops, close coordination with interdisciplinary teams, international project partners, and customers

To be well-prepared for your path, you should have the following qualifications:

• Completed studies in computer science, data science, mathematics, statistics, or a comparable field with at least 4 years of professional experience - ideally in consulting or projects in the data science, ML, or AI field
• Passion for data, AI, and Generative AI, as well as enthusiasm for their strategic added value for the business
• Expertise in Python, SQL, ETL processes, RAG, ML/DL, LLMs, Pandas, and NumPy
• Your work style is characterized by self-responsibility, goal orientation, team ability, and hands-on mentality

Worth knowing before departure:

• Start: after agreement - always at the beginning of a month
• Working hours: full-time (40 hours) and/or part-time possible; 30 vacation days
• Employment relationship: unlimited
• Field: consulting
• Language: secure German and English
• Flexibility and travel readiness
• Other: valid work permit; if necessary, we can apply for the work permit within our recruiting process. The procedure takes time and affects the start date

At MHP, you grow continuously in an innovative and supportive environment. This makes us the perfect sparring partner for your career. Both for professional input and networking. We offer you:

• Appreciation. We support and appreciate colleagues as they are and celebrate our successes together
• We are always happy about creativity and new impulses
• Flexibility. Time-wise and location-wise - according to the project at home, in the office, or at the customer
• You have the opportunity to grow with us in tasks, knowledge, and responsibility

Please apply quickly. Simply online via our Job Locator. There, you can send your application documents, such as resume, certificates, and possibly project lists, in a few clicks to us. A cover letter is not required.

By the way: If your application reaches us, our recruiting team checks across departments whether there is a suitable position for you. Regardless of current job postings, we try to find the right job for you at MHP.

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The team fosters a collaborative environment and is building a best-in-class program to partner with the business to protect the Firm’s information and computer systems. Millennium is a complex and robust technical environment and securing the Firm from external and internal threats is a top priority.

Responsibilities

• Define and implement security guardrails for Generative AI, LLMs, and Agentic frameworks, ensuring safe enterprise adoption.
• Conduct specialized threat modeling, red teaming, and risk assessments for AI/ML models (e.g., testing for prompt injection, model theft, and data poisoning).
• Lead risk management activities, including application risk assessments, design reviews, and mitigation strategies for IT projects.
• Engage throughout the SDLC to identify vulnerabilities, conduct code reviews/penetration testing, and enforce secure coding standards.
• Evangelize AppSec and AI security best practices through developer education, training materials, and outreach.
• Design robust security architectures and integrate automated security testing (SAST/DAST/SCA) into CI/CD pipelines.
• Partner with Technology, Trading, Legal, and Compliance to create policies and communicate technical risks to non-technical stakeholders.

Qualifications

• Bachelor's degree or higher in Computer Science, Computer Engineering, IT Security or related field.
• 5+ years’ experience working as an Application Security Engineer, Software Engineer, or similar role.
• Deep understanding of AI-specific risks (OWASP Top 10 for LLMs) and experience securing applications utilizing LLMs.
• Experience working with AI models, Agentic frameworks and security risks associated with AI.
• Experience in working with global teams, collaborating on code and presentations.
• Demonstrated work experience in hybrid on-premise and Public Cloud environments (AWS/GCP/Azure)
• Strong understanding of security architectures, secure configuration principles/coding practices, cryptography fundamentals and encryption protocols.
• Experience with common SCM & CI/CD technologies like GitHub, Jenkins, Artifactory, etc. and integrating Security Scanning and Vulnerability Management into the CI/CD Pipelines
• Familiarity with static and dynamic security analysis tools, and SCA/SBOM solutions.
• Hands on experience with Secrets Management & Password Vault technologies such as Delinea Secret Server and/or Hashicorp Vault, etc.
• Strong experience in secure programming in languages such as Python, Java, C++, C#, or similar.
• Familiarity with Infrastructure as Code tools (CloudFormation, Terraform, Ansible, etc.)
• Familiarity with web application security testing tools and methodologies.
• Knowledge of various security frameworks and standards such as ISO 27001, NIST, OWASP, etc.
• Knowledge of Linux, OS internals and containers is a plus.
• Certifications like CISSP, CISM, CompTIA Security+, or CEH are advantageous.

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Our team is a specialized group of engineers operating at the intersection of technology and quantitative finance. We function as an internal centre of excellence, providing expert-level solutions, architecture, and hands-on development in AI, Cloud (AWS/GCP), DevOps, and high-performance computing.

As a forward deployed software engineer, you will be responsible for translating complex research requirements into robust, scalable, and secure technical architectures across on-prem, hybrid, and cloud environments. You will write high-quality, production-ready code across the full stack, including Python libraries, infrastructure-as-code (Terraform), CI/CD pipelines, automation scripts, and ML/AI proof-of-concepts.

You will also develop and maintain our suite of managed products, reusable patterns, and best practice guides to provide self-service options and accelerate onboarding for new and existing teams. Additionally, you will act as the primary technical point of contact for embedded engagements, owning projects from discovery and planning through to implementation, knowledge transfer, and support.

To succeed in this role, you will need to have a deep understanding of computer science principles, including data structures, algorithms, and system design. You will also need to have experience working with cloud providers, such as AWS or GCP, and be familiar with infrastructure-as-code concepts. Excellent verbal and written communication skills are also essential, as you will need to build strong relationships with stakeholders and articulate complex ideas to diverse audiences.

Innovative thinking and a passion for AI/ML and its practical applications are highly desirable. Experience designing systems and architectures from ambiguous business needs, as well as experience with scheduling or asynchronous workflow frameworks/services, is also preferred.

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The successful candidate will have a proven understanding in enterprise security and AI security and will focus on defining and implementing security guardrails for Generative AI, LLMs, and Agentic frameworks, ensuring safe enterprise adoption.

Key responsibilities include:

• Defining and implementing security guardrails for Generative AI, LLMs, and Agentic frameworks
• Conducting specialized threat modeling, red teaming, and risk assessments for AI/ML models
• Leading risk management activities, including application risk assessments, design reviews, and mitigation strategies for IT projects
• Engaging throughout the SDLC to identify vulnerabilities, conduct code reviews/penetration testing, and enforce secure coding standards
• Evangelizing AppSec and AI security best practices through developer education, training materials, and outreach

Qualifications include:

• Bachelor's degree or higher in Computer Science, Computer Engineering, IT Security or related field
• 5+ years' experience working as an Application Security Engineer, Software Engineer, or similar role
• Deep understanding of AI-specific risks (OWASP Top 10 for LLMs) and experience securing applications utilizing LLMs
• Experience working with AI models, Agentic frameworks and security risks associated with AI
• Experience in working with global teams, collaborating on code and presentations

Preferred qualifications include:

• Demonstrated work experience in hybrid on-premise and Public Cloud environments (AWS/GCP/Azure)
• Strong understanding of security architectures, secure configuration principles/coding practices, cryptography fundamentals and encryption protocols
• Experience with common SCM & CI/CD technologies like GitHub, Jenkins, Artifactory, etc. and integrating Security Scanning and Vulnerability Management into the CI/CD Pipelines
• Familiarity with static and dynamic security analysis tools, and SCA/SBOM solutions
• Hands on experience with Secrets Management & Password Vault technologies such as Delinea Secret Server and/or Hashicorp Vault, etc.
• Strong experience in secure programming in languages such as Python, Java, C++, C#, or similar
• Familiarity with Infrastructure as Code tools (CloudFormation, Terraform, Ansible, etc.)
• Familiarity with web application security testing tools and methodologies
• Knowledge of various security frameworks and standards such as ISO 27001, NIST, OWASP, etc.
• Knowledge of Linux, OS internals and containers is a plus
• Certifications like CISSP, CISM, CompTIA Security+, or CEH are advantageous

We offer a competitive salary and benefits package, as well as opportunities for professional growth and development.

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Responsibilities:

• Build the core application and workflow agents for Market Data Operations in Python; integrate with AWS and internal systems like the Market Data Warehouse.
• Ingest and understand contracts at scale, using LLMs to extract costs, fee schedules, entitlements, renewal terms, and payment details.
• Connect the dots between contracts, entitlements, invoices, and payments so Ops, Legal, and Finance can see a single 'source of truth' and catch issues early.
• Design and tune LLM workflows (prompt engineering, tool/MCP integration, structured outputs) for contract Q&A, summarization, and exception flagging.
• Own monitoring and controls for the AI system: logging, metrics, guardrails, and human-in-the-loop review to keep performance, reliability, and quality high.
• Work directly with stakeholders (Market Data Ops, analysts, Legal, Finance/AP) to understand their workflows and quickly iterate on features that actually get used.

Required Skills & Experience:

• Bachelor's degree in Computer Science or a related field.
• 5+ years of professional experience with Python, including building production services (Django, Flask, or FastAPI).
• Experience working with unstructured documents (contracts, PDFs, legal docs) and turning them into structured data.
• Prompt engineering and working with structured JSON outputs
• Comfort wiring models into real applications (tool/MCP-style integrations, APIs).
• Experience using cloud platform, ideally AWS.
• Able to define and track quantitative metrics for AI features (accuracy, latency, cost, etc.).
• Strong communication skills and comfortable working directly with non-technical users.
• Enjoys a start-up-like environment inside a large firm: small team, high ownership, fast iteration.

Nice to Have:

• Experience building AI solutions in financial services, especially around market data, vendor management, or legal/contract workflows.
• Familiarity with entitlements/governance and large internal data platforms (e.g., a Market Data Warehouse).

The estimated base salary range for this position is $175,000 to $250,000, which is specific to New York and may change in the future. Millennium pays a total compensation package which includes a base salary, discretionary performance bonus, and a comprehensive benefits package.

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Our core work consists of creating custom AI applications that will impact millions of citizens, generating high-quality training data for custom LLMs, and upskilling and advisory services to spread the impact of AI.

You will serve as the lead technical strategist for public sector engagements, converting ambiguous mission requirements into robust architectural roadmaps and guiding onsite implementation.

Architect the fundamental frameworks for production-grade AI applications, setting the gold standard for how interactive UIs, backend systems, and AI models are integrated at scale to deliver reliable outcomes.

Guide the evolution of cloud infrastructure, ensuring security, global scalability, and long-term system integrity across all environments.

Direct the development of core platforms and shared services, ensuring they solve cross-cutting needs for diverse global client use cases.

Partner with cross-functional leadership to steer the technical roadmap, mentoring senior and junior staff and ensuring all products align with a cohesive, future-proof technical architecture.

Bridge the gap between the field and the core platform by turning real-world client lessons into the reusable patterns that power the entire engineering team.

Ideally, you'd have a Master's or PhD in Computer Science or equivalent deep industry experience in architecting complex, distributed systems.

10+ years of full-stack expertise across Python, Node.js, and React, with a proven track record of designing high-scale architectures on Kubernetes and global cloud infrastructures (AWS/Azure/GCP).

Expert ability to design and oversee production-grade ecosystems, ensuring world-class standards for system integrity, security, and long-term scalability.

Extensive experience deploying and troubleshooting sophisticated end-to-end solutions directly within complex, high-security client environments.

A self-driven leader capable of resolving extreme ambiguity, mentoring senior staff, and setting the technical vision for the organization.

A driver of asynchronous workflows and documentation-first cultures to streamline global engineering velocity and reduce friction.

Proficient in Arabic.

Nice to haves include past experience working at a startup as a CTO or founding engineer or in a forward deployed engineer / dedicated customer engineer role, experience working cross functionally with operations, and a proven track record of building LLM-driven solutions with the strategic foresight to anticipate landscape shifts and architect future-proof systems.

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Our core work consists of creating custom AI applications that will impact millions of citizens, generating high-quality training data for custom LLMs, and upskilling and advisory services to spread the impact of AI.

As a Full Stack Software Engineer (Forward Deployed), you'll collaborate directly with public sector counterparts to quickly build full-stack, AI applications, to solve their most pressing challenges and achieve meaningful impact for citizens.

At Scale, we're not just building AI solutions,we're enabling the public sector to transform their operations and better serve citizens through cutting-edge technology.

Responsibilities:

• Collaborate with senior engineers to implement features for public sector clients, including spending time with the client to understand user feedback and assist with delivery.
• Develop and maintain full-stack components that integrate with AI models, focusing on building responsive UIs and reliable backend APIs.
• Assist in deploying and monitoring applications within cloud environments, ensuring basic system stability and security.
• Help build and refine reusable features that support diverse international client use cases.
• Work within a multi-disciplinary team of design, product, and data specialists to build robust features that follow established technical architectures.

Ideal Candidate:

• Bachelor's degree in Computer Science or a related quantitative field
• Professional full-stack experience with a focus on React, TypeScript, and Python/Node.js. Familiarity with Next.js and NoSQL/Relational databases, along with exposure to containerization (Docker) and cloud deployments.
• Experience building and deploying web applications with a good understanding of cloud fundamentals and scalable coding practices.
• A self-starting approach to navigate ambiguous requirements and deliver reliable software.

Nice to Have:

• Proficient in Arabic
• Experience working cross functionally with operations
• Experience building solutions with LLMs

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This is a 0→1 build team. We’re looking for a sharp, product-minded Senior Engineer who thrives in ambiguity, moves quickly, and enjoys building new systems from scratch alongside customers and cross-functional partners. You’ll work closely with product, forward-deployed engineers, data scientists, and applied AI teams to turn real-world problems into scalable, production solutions.

If you like shipping fast, owning outcomes, and working across the stack,from polished frontends to distributed backends to LLM integrations,this role is for you.

Responsibilities

• Own major full-stack product areas, driving features from concept and design through production deployment
• Build intuitive, high-performance frontend experiences using React + TypeScript
• Develop reliable backend services in Python, working with distributed systems, data pipelines, and AI/ML infrastructure
• Integrate LLMs, vector databases, and agentic frameworks to power intelligent workflows and decision-making systems
• Ship quickly through tight experimentation loops while maintaining high quality and reliability
• Help define the technical direction and architecture of a brand-new team and product surface
• Adapt across the stack and learn new tools as needed to solve real problems end-to-end

Ideal Experience

• 5+ years of full-time software engineering experience
• 0-1 product build experience
• Familiarity with LLMs, embeddings, vector databases, or modern AI data products/tools
• Experience with distributed systems and cloud-based architectures
• Prior experience mentoring or leading team

What We Value

• Strong product intuition and customer empathy
• Bias toward action and rapid iteration
• Ownership mentality , you see problems through to outcomes
• Comfort collaborating across engineering, product, data science, and applied AI
• Excitement about building agentic systems that make AI genuinely useful in the real world

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Daily data-driven experiments will provide key insights around model strengths and inefficiencies which you'll use to improve your product's performance. If you are excited about shaping the future of the modern AI movement, we would love to hear from you!

You will:

• Own, plan, and optimize the AI behind our Enterprise customer's deepest technical problems
• Leverage SGP to build the most advanced AI agents across the industry including multimodal functionality, tool-calling, and more
• Have experience gathering business requirements and translating them into technical solutions
• Meet regularly with customer teams onsite and virtually, collaborating cross-functionally with all teams responsible for their data and ML needs
• Push production code in multiple development environments, writing and debugging code directly in both our customer's and Scale's codebases.

Ideally you'd have:

• 7+ years of full-time engineering experience, post-graduation
• A love for solving deeply complex technical problems with ambiguity using state of the art research and AI to accomplish your client’s business goals
• Strong engineering background: a Bachelor’s degree in Computer Science, Mathematics, or another quantitative field or equivalent strong engineering background.
• Deep familiarity with a data-driven approach when iterating on machine learning models and how changes in datasets can influence model results
• Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment
• Proficiency in Python to write, test and debug code using common libraries (ie numpy, pandas)

Nice to haves:

• Strong knowledge of software engineering best practices
• Have built applications taking advantage of Generative AI in real, production use cases
• Familiarity with state of the art LLMs and their strengths/weaknesses

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Key Responsibilities: Lead and mentor a high-performing engineering team of 50+, fostering a culture of technical excellence and ownership. Guide your team through complex challenges involving LLMs, AI agents, and large-scale distributed systems. Represent Scale AI in high-stakes negotiations and strategic discussions with senior external partners, demonstrating strong technical competence and credibility. Develop and communicate a compelling vision for Scale AI’s technology applied to your program. Provide regular updates to senior leadership and key stakeholders on progress, risks, and opportunities. Foster a culture of speed, unity of purpose, resilience, and teamwork.

Requirements: 10+ years of software engineering experience, including 5+ years in a technical leadership or staff role. Deep understanding of modern AI/ML technologies, including experience working with LLMs and AI agents. Proficient in one or more modern programming languages (Python, JavaScript/TypeScript). Hands-on experience with Kubernetes and cloud infrastructure (AWS, GCP, or Azure). Strong product and business sense, with a track record of aligning engineering efforts with company goals. Ability to operate effectively in ambiguous, fast-changing environments and guide your team to do the same. Experience in executive level engagement with industry partners and Public Sector customers

Success Metrics: Within 6 months: Successful demonstration of agentic AI’s mission value in high-stakes customer demonstrations Establish Scale AI as the preferred agentic AI partner for the PEO Establish high velocity, agile engineering cadence both internally and with our industry partners

Within 12–18 months: Secure follow-on contract award with expanded scope for Scale Position Scale AI as the global AI leader in this mission area Establish developed solutions as Scale product offerings to deliver on future contracts

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training.

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Key responsibilities include:

• Delivering experiments at a high velocity and level of quality to engage our customers
• Working across the entire product lifecycle from conceptualization through production
• Being able, and willing, to multi-task and learn new technologies quickly

Ideally, you'd have:

• 7+ years of full-time engineering experience, post-graduation
• Experience scaling products at hyper growth startups
• Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies
• Proficient in Python or Javascript/Typescript, and SQL
• Experience with Kubernetes
• Experience with major cloud providers (AWS, Azure, GCP)

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training.

You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

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You will be responsible for owning large new areas within our product, working across backend, frontend, and interacting with LLMs and ML models. You will solve hard engineering problems in scalability and reliability.

Key responsibilities include:

• Owning large new areas within our product
• Working across backend, frontend, and interacting with LLMs and ML models
• Delivering experiments at a high velocity and level of quality to engage our customers
• Working across the entire product lifecycle from conceptualization through production

Ideally, you'd have:

• 4+ years of full-time engineering experience, post-graduation
• Experience scaling products at hyper growth startups
• Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies
• Proficient in Python or Javascript/Typescript, and SQL
• Experience with Kubernetes
• Experience with major cloud providers (AWS, Azure, GCP)

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training.

You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

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This high-impact role will drive the technical direction and oversight for Deep Research Agent Development, translating cutting-edge research in Generative AI, Large Language Models (LLMs), and Agentic Frameworks into robust, scalable, and high-impact production systems that enhance enterprise operations, analytics, and core efficiency.

The ideal candidate thrives in a fast-paced environment, has a passion for both deep technical work and mentoring, and is capable of setting a long-term technical strategy for a critical domain while maintaining a strong, hands-on delivery focus.

Responsibilities

Technical Leadership & Vision

• Set the Technical Roadmap: Define and own the technical strategy, architecture, and roadmap for Deep Research Agents for the Enterprise, ensuring alignment with Scale AI’s overall AI strategy and business goals.

• Drive Breakthrough Research to Production: Lead the end-to-end development, from initial research to production deployment, to landing on customer impact, with a focus on integrating diverse data modalities.

• Core Agent Capabilities Development:

Advanced Knowledge Retrieval: Architect and implement state-of-the-art retrieval systems to ensure the agents provide accurate and comprehensive answers from public and proprietary data sources from enterprises.

Data Analysis: Design and champion the development of data analysis agents that accurately translate complex natural language queries into executable SQL/code against diverse enterprise data schemas.

Multimodal Intelligence: Lead the integration of Multimodal AI capabilities to process and extract structured information from visual documents, tables, and forms, enriching the agent's knowledge base.

Architecture & Design: Design and champion highly scalable, reliable, and low-latency infrastructure and frameworks for building, orchestrating, and evaluating multi-agent systems at enterprise scale.

Technical Excellence: Serve as the technical authority for the team, leading design reviews, defining ML engineering best practices, and ensuring code quality, security, and operational excellence for all agent systems.

Team Leadership & Mentorship

• Lead and Mentor: Technically lead and mentor a team of Machine Learning Engineers and Research Scientists, fostering a culture of innovation, rigorous engineering, rapid iteration, and technical depth.

• Recruiting & Growth: Partner with management to hire, onboard, and grow top-tier talent, helping to shape the long-term structure and capabilities of the team.

• Cross-Functional Influence: Collaborate effectively with Product Managers, Data Scientists, and other engineering/science teams to translate ambiguous, high-level business problems into concrete, executable technical specifications and impactful agent solutions.

Basic Qualifications

• Bachelor's degree in Computer Science, Electrical Engineering, a related field, or equivalent practical experience.

• 8+ years of experience in software development, with at least 6 years focused on Machine Learning, Deep Learning, or Applied Research in a production environment.

• 2+ years of experience in a formal or informal Technical Leadership role (Team Lead, Tech Lead) with a focus on setting technical direction for a domain.

• Deep expertise in Generative AI and Large Language Models (LLMs).

• Demonstrated experience designing, building, and deploying AI Agents or complex Agentic systems in production at scale.

• Experience with large-scale distributed systems and real-time data processing.

Preferred Qualifications

• Advanced degree (Master's or Ph.D.) in Computer Science, Machine Learning, or a related quantitative field.

• Demonstrated experience designing and deploying production-grade Text-to-SQL systems, including handling complex schema linking and query optimization.

• Practical experience with Multimodal AI, specifically integrating OCR and vision-language models for document intelligence and structured data extraction from images/forms.

• Proven experience in one or more relevant deep research areas: Reinforcement Learning (RL), Reasoning and Planning, Agentic Systems.

• Experience with vector databases and advanced retrieval techniques.

• A track record of publishing research papers in top-tier ML/AI conferences (e.g., NeurIPS, ICML, ICLR, KDD).

• Excellent written and verbal communication skills, with the ability to articulate complex technical vision to executive stakeholders and technical peers.

• Experience driving cross-team technical initiatives that have delivered significant business impact.

Compensation

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity-based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

About Us

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.

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This is not a traditional analytics role. On this team, data scientists do the core statistical and modeling work, but they also build real tools and products: evaluation explorers, operator workflows, decision-support systems, experimentation surfaces, and customer-specific AI/data applications that get used in production.

The right candidate is strong in first-principles problem solving, rigorous measurement, and technical execution. They know how to define metrics, design experiments, diagnose failures, and build systems that people actually use. They are also comfortable using modern AI-assisted development tools to prototype and iterate quickly without sacrificing reliability, observability, or judgment. Python and SQL matter in this role, but as execution fluency in service of building better products and making better decisions.

Responsibilities: Partner directly with enterprise customers to understand workflows, operational pain points, constraints, and success criteria Turn ambiguous business and product problems into measurable solutions with clear metrics, technical designs, and deployment plans Design and build internal and customer-facing data products, including evaluation tools, workflow applications, decision-support systems, and thin product layers on top of data/ML systems Build end-to-end solutions across data ingestion, transformation, experimentation, statistical modeling, deployment, monitoring, and iteration Design evaluation frameworks, benchmarks, and feedback loops for ML/LLM systems, human-in-the-loop workflows, and model-assisted operations Apply rigorous statistical thinking to experimentation, causal inference, metric design, forecasting, segmentation, diagnostics, and performance measurement Use AI-assisted development workflows to accelerate prototyping and product iteration, while maintaining strong engineering discipline Diagnose failure modes across data quality, model behavior, retrieval, workflow design, and user experience, and drive fixes into production Act as the voice of the customer to Product, Engineering, and Data Science, using field learnings to shape roadmap and platform capabilities

Requirements: 5+ years of experience in data science, machine learning, quantitative engineering, or another highly analytical technical role Proven track record of shipping data, ML, or AI systems that delivered measurable business or product impact Exceptional ability to structure ambiguous problems, define the right success metrics, and translate them into executable technical plans Strong foundation in statistics, experimentation, causal reasoning, and measurement Experience building tools or products, not just analyses , for example internal workflow tools, evaluation systems, operator-facing products, experimentation platforms, or customer-specific applications Hands-on fluency in Python, SQL, and modern data/AI tooling; able to inspect data, prototype quickly, debug deeply, and productionize solutions that work Comfort using AI-assisted coding and development workflows to move from idea to usable product quickly Strong communication and stakeholder management skills; able to work effectively with customers, engineers, product teams, and executives High ownership and bias toward shipping in fast-moving environments with incomplete information

Preferred qualifications: Experience in a forward deployed, solutions, consulting, or other client-facing technical role Experience designing evaluation frameworks for LLMs, retrieval systems, agentic workflows, or other AI-enabled products Experience with large-scale data processing and distributed systems such as Spark, Ray, or Airflow Experience with cloud infrastructure and modern data platforms such as AWS, GCP, Snowflake, or BigQuery Experience building lightweight applications, APIs, internal tools, or workflow software on top of data/ML systems Familiarity with marketplace experimentation, causal inference, forecasting, optimization, or advanced statistical modeling Strong product instinct and the judgment to know when the right answer is a model, an experiment, a tool, or a workflow redesign

What success looks like: Success in this role means taking a messy, high-stakes customer problem and turning it into a deployed system that is actually used. Sometimes that system is a model. Sometimes it is an evaluation framework. Sometimes it is an operator-facing tool or a lightweight data product that changes how decisions get made. In all cases, success is defined by measurable impact, rigorous evaluation, and reliable execution.

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

Salary Range: $167,200-$209,000 USD

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This role sits at the intersection of product thinking and full-stack engineering. You'll work directly with researchers and engineers to deeply understand their workflows, identify bottlenecks, and rapidly ship solutions that multiply their productivity. Whether you're building human feedback interfaces for model evaluation, creating platforms for experiment orchestration, or developing novel visualization tools for understanding model behavior, your work will directly accelerate our mission to build safe, reliable AI systems.

We're looking for someone who can operate with high agency in an ambiguous environment,someone who can be dropped into a research team, quickly develop domain expertise, and independently drive impactful projects from conception to delivery.

Responsibilities:

• Build and maintain full-stack applications and infrastructure that researchers use daily to conduct experiments, collect feedback, and analyze results
• Partner closely with research teams to understand their workflows, pain points, and requirements, translating these into technical solutions
• Design intuitive interfaces and abstractions that make complex research tasks accessible and efficient
• Create reusable platforms and tools that accelerate the development of new research applications
• Rapidly prototype and iterate on solutions, gathering feedback from users and refining based on real-world usage
• Take ownership of complete product areas, from understanding user needs through design, implementation, and ongoing iteration
• Contribute to technical strategy and architectural decisions for research tooling
• Mentor other engineers and help establish best practices for research application development

Requirements:

• 5+ years of software engineering experience with a strong focus on full-stack development
• Excel at rapid iteration and shipping,you can move from concept to working prototype quickly
• Have experience building tools, platforms, or infrastructure for technical users (engineers, researchers, data scientists, analysts, etc.)
• Demonstrate high agency and ability to operate independently in ambiguous environments
• Can quickly develop deep understanding of complex technical domains
• Have strong product instincts and can identify the right problems to solve
• Are proficient with modern web technologies (React, TypeScript, Python, etc.)
• Have a track record of building user-facing applications that are actually used and loved by their target audience
• Communicate effectively with both technical and non-technical stakeholders
• Care about the societal impacts of your work and are motivated by Anthropic's mission

Strong candidates may also have:

• Experience building research tools, scientific software, or experimentation platforms
• Background in machine learning, AI research, or working closely with ML researchers
• Founded or been an early engineer at a startup, particularly one focused on developer or researcher tools
• Built open-source tools or platforms with active user communities
• Experience with data visualization, interactive interfaces, or novel interaction paradigms
• Contributed to engineering platforms or internal tooling at scale (similar to Heroku, Vercel, or other platform-as-a-service products)
• Experience leveraging AI/LLMs to build more powerful or efficient tools
• Previous work in creative tools, artist tools, or other domains requiring deep user empathy
• Domain knowledge in areas like human-computer interaction, systems safety, or AI alignment

Annual compensation range for this role is $300,000-$405,000 USD.

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This is a hands-on technical role that combines deep engineering expertise with customer-facing problem solving. You'll work directly with customer engineering teams to integrate AI into their critical workflows.

Key Responsibilities

Customer Integration & Deployment

• Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements
• Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs)
• Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows
• Deploy and configure AI models and agents within customer security and compliance boundaries

AI Agent Development

• Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation
• Architect multi-agent systems that orchestrate between different models, tools, and data sources
• Implement evaluation frameworks to measure agent performance and iterate toward business objectives
• Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement

Prompt Engineering & Optimization

• Create sophisticated prompt engineering strategies optimized for customer-specific domains and data
• Build and maintain prompt libraries, templates, and best practices for customer use cases
• Conduct systematic prompt experimentation and A/B testing to improve model outputs
• Implement RAG (Retrieval Augmented Generation) systems and fine-tuning pipelines where appropriate

Technical Leadership & Collaboration

• Serve as the primary technical point of contact for strategic enterprise accounts
• Collaborate with customer data scientists, ML engineers, and software developers to ensure smooth integration
• Provide technical training and knowledge transfer to customer teams
• Work closely with Scale's product and engineering teams to translate customer needs into product improvements
• Document technical architectures, integration patterns, and best practices

Problem Solving & Innovation

• Debug complex technical issues across the entire stack, from data pipelines to model outputs
• Rapidly prototype solutions to unblock customers and prove out new use cases
• Stay current on the latest AI/ML research and tools, bringing innovative approaches to customer problems
• Identify opportunities for productization based on common customer patterns

Required Qualifications

• 4+ years of software engineering experience with strong fundamentals in data structures, algorithms, and system design
• Production Python expertise with experience in modern ML/AI frameworks (e.g., LangChain, LlamaIndex, HuggingFace, OpenAI API)
• Experience with cloud platforms (AWS, GCP, or Azure) and modern data infrastructure
• Strong problem-solving skills with the ability to navigate ambiguous requirements and rapidly iterate toward solutions
• Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences

Preferred Qualifications

• Agent Development Wiz
• Deep understanding of LLMs including prompting techniques, embeddings, and RAG architectures
• Experience building and deploying AI agents or autonomous systems in production
• Knowledge of vector databases and semantic search systems
• Contributions to open-source AI/ML projects

• Infrastructure Guru
• Experience with containerization (Docker, Kubernetes) and CI/CD pipelines
• Experience using Terraform, Bicep, or other Infrastructure as Code (IaC) tools
• Previous work in a devops, platform, or infra role

• Customer Product Whisperer
• Proven ability to work with customers in a technical consulting, solutions engineering, or product engineering role
• Domain expertise in verticals like finance, healthcare, government, or manufacturing
• Experience with technical enablement or teaching programs

Sample Projects

The following are some examples of the types of projects we’ve worked on with customers. All of these projects leverage customer data, integrate directly into customers’ existing systems, and are deployed on their infrastructure.

• Deep Research for Due Diligence
• Churn Prediction
• Data Extraction Voice Agent

Compensation

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

Pay Transparency

For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $216,000-$270,000 USD

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At Scale AI, our mission is to accelerate the development of AI applications. This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents.

Responsibilities

• Explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation.
• Contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate these advancements into real-world, scalable solutions.

Requirements

• Practical experience working with LLMs, with proficiency in frameworks like Pytorch, Jax, or Tensorflow.
• A track record of published research in top ML venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, COLM, etc.).
• At least three years of experience addressing sophisticated ML problems, either in a research setting or product development.

Nice to Have

• Hands-on experience with open source LLM fine-tuning or involvement in bespoke LLM fine-tuning projects using Pytorch/Jax.
• Hands-on experience and publications in building applications and evaluations related to AI agents such as tool-use, text2SQL, browser agents, coding agents and GUI agents.
• Hands-on experience with agent frameworks such as OpenHands, Swarm, LangGraph, etc.
• Familiarity with agentic reasoning methods such as STaR and PLANSEARCH
• Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment.

Benefits

• Comprehensive health, dental and vision coverage
• Retirement benefits
• A learning and development stipend
• Generous PTO
• Commuter stipend

Salary Range

$259,200-$324,000 USD

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As the Engineering Manager for Lakeflow Designer, you will lead a seed team of engineers to build a brand new Visual and AI-first editing experience for Databricks SQL. You will play a pivotal role in bringing this product from its current Private Preview stage to General Availability (GA) in the next 6-9 months. You will be responsible for scaling the team from its current size of ~6 engineers to 10-15 over the next year.

This is a high-visibility frontend-focused role where you will guide the development of intuitive user experiences and embedded agentic assistants that have the potential to completely change how customers interact with and analyze data on the platform.

Key responsibilities include:

• Leading product launch: Drive the roadmap and execution to launch Lakeflow Designer to General Availability (GA) within 6-9 months, ensuring we bring the product to market and delight users.
• Scaling the team: Rapidly hire and build out the team in a fast-moving area, growing the engineering headcount to 10-15 members.
• Driving technical & UX strategy: Oversee a frontend-heavy technology stack (React, TypeScript), championing high-quality UX and the integration of Gen AI/LLMs to build agentic capabilities.
• Unlocking data insights: Build an experience that opens up the platform to a broader, less technical audience, enabling entire new categories of customers to get insights from their data.
• Cross-functional collaboration: Partner closely with a strong Technical Lead, Product Management, and Design team to define the product vision and ensure successful execution.

Requirements include:

• 10+ years of software engineering experience, with a strong track record of technical leadership and impact.
• 5+ years of Engineering Leadership: Experience leading frontend teams, with a proven ability to manage and grow high-performing engineering groups.
• Frontend expertise: Strong technical background in React, TypeScript, and JavaScript.
• Product & UX passion: A strong passion for product and user experience; you care deeply about how users interact with the tool.
• Zero-to-one experience: Experience bringing a product from 'zero to one' is a significant plus.
• AI/LLM interest: Experience building Agents and working with LLMs is a bonus.
• Fast-paced execution: Ability to thrive in a fast-moving environment, specifically with experience hiring and scaling teams rapidly.

Why join us?

• Redefine SQL authoring: SQL is the main way our customers interact with their data; this role offers the chance to completely change how customers write SQL across the Databricks platform.
• Intersection of AI and UX: Work at the cutting edge of Gen AI, building agentic assistants that genuinely simplify complex workflows.
• High impact: Lead a team that is building a product with the potential to unlock data insights for vastly more users than what is possible today with raw SQL or notebooks.

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At Scale, our mission is to accelerate the development of AI applications. We're looking for a Machine Learning Research Scientist/Engineer to join our team and help us shape the future of AI.

This role operates at the forefront of AI research and real-world implementation, with a strong focus on reasoning within large language models (LLMs). You will study the data types critical for advancing LLM-based agents, including browser and software engineering (SWE) agents. You will play a key role in shaping Scale's data strategy by identifying the most effective data sources and methodologies for improving LLM reasoning.

Success in this role requires a deep understanding of LLMs, planning algorithms, and novel approaches to agentic reasoning, as well as creativity in tackling challenges related to data generation, model interaction, and evaluation. You will contribute to impactful research on language model reasoning, collaborate with external researchers, and work closely with engineering teams to bring state-of-the-art advancements into scalable, real-world solutions.

Responsibilities

• Study the data types critical for advancing LLM-based agents, including browser and software engineering (SWE) agents
• Shape Scale's data strategy by identifying the most effective data sources and methodologies for improving LLM reasoning
• Contribute to impactful research on language model reasoning
• Collaborate with external researchers
• Work closely with engineering teams to bring state-of-the-art advancements into scalable, real-world solutions

Requirements

• Practical experience working with LLMs, with proficiency in frameworks like PyTorch, JAX, or TensorFlow
• A track record of published research in top ML and NLP venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, CoLLM, etc.)
• At least three years of experience solving complex ML challenges, either in a research setting or product development, particularly in areas related to LLM capabilities and reasoning
• Strong written and verbal communication skills, along with the ability to work effectively across teams

Nice to Have

• Hands-on experience fine-tuning open-source LLMs or leading bespoke LLM fine-tuning projects using PyTorch/JAX
• Research and practical experience in building applications and evaluations related to LLM-based agents, including tool-use, text-to-SQL, browser agents, coding agents, and GUI agents
• Experience with agent frameworks such as OpenHands, Swarm, LangGraph, or similar
• Familiarity with advanced agentic reasoning techniques such as STaR and PLANSEARCH
• Proficiency in cloud-based ML development, with experience in AWS or GCP environments

Benefits

• Comprehensive health, dental and vision coverage
• Retirement benefits
• A learning and development stipend
• Generous PTO
• Commuter stipend

Salary Range

$252,000-$315,000 USD

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Responsibilities

• Own major full-stack product areas, driving features from design through production deployment.
• Build modern frontend experiences using React and TypeScript, ensuring performance, usability, and responsiveness.
• Develop reliable backend services in Python, working with distributed systems, data pipelines, and ML/LLM components.
• Integrate with LLMs, vector databases, and AI infrastructure to power intelligent product experiences.
• Deliver experiments and new features quickly, maintaining high quality and tight feedback loops with customers.
• Collaborate across product, ML, and infrastructure teams to shape the direction of Scale GP.
• Adapt quickly,learning new technologies, frameworks, and tools as needed across the stack.

Ideal Experience

• 5+ years of full-time engineering experience, post-graduation.
• Strong experience developing full-stack applications using React, TypeScript, and Python.
• Experience scaling or shipping products at high-growth startups.
• Familiarity with LLMs, vector databases, embeddings, or other modern AI tooling (tinkering or production experience welcome).
• Proficiency with SQL and modern API development.
• Experience with Kubernetes, containerization, and microservice architectures.
• Experience working with at least one major cloud provider (AWS, GCP, or Azure).

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

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You'll help define the future of content at Databricks by making it a first-class product experience and integrating content development into product development.

Key responsibilities include:

• Owning the content experience end-to-end, ensuring it's helpful, intuitive, and actionable
• Driving strategic improvements to content tooling and workflows
• Building an architecture of participation that enables context experts to contribute directly to content
• Integrating AI to transform content experiences
• Defining metrics that matter and tracking content engagement, time-to-task, support deflection, and user satisfaction

Requirements include:

• 7+ years of product management experience, with a proven track record of leading cross-functional initiatives and delivering high-impact user experiences
• Deep understanding of developer tools, data platforms, or technical products with large surface areas
• Strong systems mindset, comfortable designing scalable workflows, content architectures, and tooling integrations
• Experience with developer documentation, content platforms, or product onboarding is a plus
• Strong customer empathy and an obsession with helping users succeed
• Familiarity with AI technologies (especially LLMs) and how they can be applied to content workflows and user guidance
• Experience working with technical and non-technical contributors in a collaborative content ecosystem

Pay Range Transparency: Databricks is committed to fair and equitable compensation practices. The pay range for this role is $181,700-$249,800 USD.

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You will work with Solution Architects to guide customers in architecting production-grade ML & AI applications on Databricks, while aligning their technical roadmap with the continually evolving Databricks Data Intelligence Platform.

You will continue to strengthen your technical skills through applying cutting-edge technologies in GenAI, MLOps, and ML more broadly, expanding your impact through mentorship, and establishing yourself as an AI thought leader.

The impact you will have:

• Architect production-level ML & AI workloads for customers using our unified platform, including agents, end-to-end ML pipelines, training/inference optimisation, integration with cloud-native services, MLOps, etc.

• Serve as trusted practitioner for enterprise GenAI solutions, including RAG architectures, agentic systems (tool-calling agents, multi-agent orchestration, guardrails), natural language querying of structured data, AI evaluation and observability, and monitoring systems

• Build, scale, and optimise customer AI workloads and apply best-in-class MLOps to productionise these workloads across a variety of domains

• Provide advanced technical support to Solution Architects during the technical sale ranging from feature engineering, training, tracking, serving to model monitoring all within a single platform, as well as participating in the larger ML SME community in Databricks

• Collaborate cross-functionally with the product and engineering teams to represent the voice of the customer, define priorities and influence the product roadmap, helping with the adoption of Databricks' AI offerings

What we look for:

• 5+ years of hands-on industry ML experience in at least one of the following:

• ML Engineer: Build and maintain production-grade cloud (AWS/Azure/GCP) infrastructure that supports the deployment of ML applications, including drift monitoring.

• AI Engineer: Experience with the latest techniques in LLMs & agentic systems including vector databases, fine-tuning LLMs, AI guardrail systems, and deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI

• Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience

• Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike

• Passion for collaboration, life-long learning, and driving business value through ML & AI

• [Preferred] 2+ years customer-facing experience in a pre-sales or post-sales role

• Can meet expectations for technical training and role-specific outcomes within 3 months of hire

• This role can be remote, but we prefer that you be located in the job listing area and can travel up to 30% when needed

Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilising the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here. Local Pay Range $219,100-$301,300 USD

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Lead applied ML engineering on Scale's Applied ML team, powering data infrastructure for leading agentic LLMs (ChatGPT, Gemini, Llama). You will build scalable multi-agent systems to validate agentic reasoning and behaviours, scale human expertise, and drive research into real-world agent reliability failures despite strong benchmarks, shipping production fixes.

Responsibilities

• Build and deploy multi-agent systems for agentic reasoning validation
• Develop pipelines to detect errors and scale human judgment
• Combine classical ML, LLMs, and multi-agent techniques for reliability
• Lead research into agent failure modes and ship fixes
• Use AI tools to speed prototyping and iteration
• Build data-driven evaluations and deploy rapid improvements
• Integrate systems into Scale's platform

Ideal Candidate

• PhD or MSc in Computer Science, Mathematics, Statistics, or related field
• 3+ years shipping scaled production ML systems
• Demonstrated real-world impact
• Mastery of PyTorch, TensorFlow, JAX, or scikit-learn
• Deep expertise in agentic LLMs and multi-agent systems
• Strong software engineering and microservices (AWS/GCP)
• Rapid, data-driven iteration
• Proficiency using AI tools to accelerate work
• Strong research depth with practical bias
• Excellent cross-functional communication

Nice to Have

• Experience prototyping agent evaluation/reliability systems
• Human-in-the-loop or annotation pipeline work
• Open-source contributions in agents, evaluation, or alignment
• Publications on agent reliability (NeurIPS, ICML, ICLR)

Compensation

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity-based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

About Us

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.

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As part of our Merchant team, you'll work across Engineering, Data Science, Product Marketing, and Design to deliver industry-leading AI and ML solutions, including the use of LLMs, to identify and surface relevant, high-quality merchants across all segments.

This will help Pinners discover new brands, increasing their confidence and consideration for shopping, while helping our merchants build new, diverse audiences.

You'll ship impactful models and experiences which direct high-traffic Pinterest surfaces, including both organic and paid, playing a key role in Pinterest's top strategic theme for the years ahead.

Responsibilities:

• Define, design, and launch thoughtful AI/ML-powered experiences that help users discover, curate, and shop ideas tailored to their unique taste.

• Partner cross-functionally with Engineering, Design, and Data Science to craft seamless and delightful experiences at the intersection of user experience, ML, and AI.

• Set product vision, influence strategy, write requirements, develop hypotheses, and establish success metrics for critical personalization initiatives.

• Identify and prioritize new opportunities to advance the relevance, impact, and sophistication of personalization across Pinterest's Curation portfolio.

• Autonomously navigate and resolve complex, ambiguous product challenges,and influence product strategy across multiple teams.

Requirements:

• Track record in AI/ML products: Experience building and launching personalized experiences, ideally at scale, for e-commerce platforms.

• Technical fluency: Strong understanding of AI/ML product development; usage of LLMs for scale, ability to credibly partner with engineers and data scientists across the stack.

• Strong product discovery skills: You're comfortable talking to business customers, mapping workflows, validating problems, and translating insights into clear product strategies and roadmaps.

• Sharp communication: Comfortable presenting to executives and cross-functional audiences; excels at simplifying complex technical and product concepts to drive clear decisions.

• Comfort with ambiguity and a bias for action: You can bring clarity to ambiguous problem spaces and move quickly while keeping stakeholders informed.

• Strategic and customer-centric: Deep empathy for user needs, with an ability to turn rich data and insights into new opportunities and delightful features.

• Ecosystem Understanding: Strong experience in B2B2C or “dual-customer” operating models to deliver delightful experiences for multiple stakeholders.

• Collaborative influencer: Ability to build trusted relationships with a variety of internal partners (including Advanced Technology, Product Marketing, Sales, Trust & Safety, Monetization, and more) and align them to shared goals.

• Ownership mindset: Skilled at defining what success looks like, rallying teams, and guiding projects from ideation to successful launch.

• Bachelor’s degree in a relevant field such as Computer Science, or equivalent experience.

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The ideal candidate thrives in a fast-paced environment, has a passion for both deep technical work and mentoring, and is capable of setting a long-term technical strategy for a critical domain while maintaining a strong, hands-on delivery focus.

You will architect and implement solutions across multiple cloud providers (GCP, Azure, AWS) for customers in diverse, highly-regulated industries like healthcare, telecom, finance, and retail.

Key responsibilities include:

• Architecting multi-cloud systems and abstractions to allow the SGP platform to run on top of existing Cloud providers.
• Using our own data and AI platform to analyse build and test logs and metrics to identify areas for improvement.
• Defining the architectural patterns for our multi-cloud infrastructure to support secure, reliable, and scalable Agentic workflows for enterprise customers.
• Enhancing engineering and infrastructure efficiency, reliability, accuracy, and response times, including CI/CD processes, test frameworks, data quality assurance, end-to-end reconciliation, and anomaly detection.
• Collaborating with platform and product teams to develop and implement innovative infrastructure that scales to meet evolving needs.
• Designing and championing highly scalable, reliable, and low-latency infrastructure and frameworks for building, orchestrating, and evaluating multi-agent systems at enterprise scale.
• Leading the infrastructure roadmap with a strong focus on compliance, privacy, and security standards, including designing change management and data isolation strategies.
• Owning the development and maintenance of our best-in-class Agentic observability platform (logging, metrics, tracing, and analytics) to proactively ensure system health and enable rapid incident response.
• Driving developer efficiency by building automated tooling and championing Infrastructure-as-Code (IaC) paradigms throughout the engineering organization to improve workflows and operational efficiency.

The ideal candidate has proven experience in a senior role, with 5+ years of full-time software engineering experience, and a deep understanding of modern infrastructure practices, including CI/CD, IaC (e.g., Terraform, Helm Charts), container orchestration (e.g., Kubernetes) and observability platforms (e.g., Datadog, Prometheus, Grafana).

Extensive experience with at least one major cloud provider (AWS, Azure, or GCP) and strong knowledge of security and compliance in enterprise environments, with a focus on access management, data isolation, and customer-specific VPC setups is required.

Proficiency in Python or JavaScript/TypeScript, and SQL is also necessary.

Bonus points for hands-on experience and a passion for working with Agents, LLMs, vector databases, and other emerging AI technologies.

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As a Senior Product Designer, you will be an important part of the Design team, partnering with other designers and cross-functional teammates on features across our mobile apps, website, and communications.

Key responsibilities include designing and prototyping simple, playful learning experiences for the Duolingo app, driving large work streams across your team with independence, and working with other designers and artists to expand Duolingo's design language.

You will also partner with engineers and product managers to define what we build, and how we get there, considering every part of a finely crafted experience: animation, copy, UI to business impact.

We care deeply about craft, so you will grow your skills while contributing to work that's both user-friendly and fun, sweating the details to get them just right.

You will join a culture of creativity and craft, where we have a high bar for excellence and an endless curiosity about how to bring more unexpected quirk and fun to the pursuit of learning.

If you're looking for a challenging and rewarding role where you can make a meaningful impact, we encourage you to apply.

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You will work across the full agent lifecycle,from model and system design to evaluation, deployment, and iteration,bridging cutting-edge agentic techniques with the constraints and requirements of real customer environments.

Key responsibilities include:

• Design and implement end-to-end agent systems that combine LLM reasoning, tool use, memory, and control logic to solve recurring enterprise use cases.
• Build scalable, reliable agent architectures that can be deployed across many customers with varying data, tools, and constraints.
• Develop evaluation frameworks, datasets, environments, and metrics to measure agent performance, reliability, and business impact in production settings.
• Collaborate closely with product managers, customers, data annotators, and other engineering teams to translate enterprise requirements into robust agent designs.
• Productionize frontier agent techniques (e.g., planning, multi-step reasoning and tool-use, multi-agent patterns) into maintainable, observable systems.
• Own deployment, monitoring, and iteration of agent systems, including failure analysis and continuous improvement based on real-world usage.
• Contribute to technical direction and architectural decisions for general agent development best practices and methods, with increasing scope and leadership at the Staff level.

Ideal candidates will have:

• 5+ years of experience building and deploying machine learning or AI systems for real-world, production use cases.
• Strong engineering fundamentals, supported by a Bachelor’s and/or Master’s degree in Computer Science, Machine Learning, AI, or equivalent practical experience.
• Deep understanding of modern LLMs, prompt-, context-, and system-level optimization, and agentic system design.
• Proven proficiency in Python, including writing production-quality, testable, and maintainable code.
• Experience building systems that integrate models with external tools, APIs, databases, and services.
• Ability to operate in ambiguous problem spaces, balancing research-driven approaches with pragmatic product constraints.
• Strong communication skills and comfort working in customer-facing or cross-functional environments.

Nice-to-haves include hands-on experience building AI agents using modern generative AI stacks, experience with agent frameworks, orchestration layers, or workflow systems, familiarity with evaluation, monitoring, and observability for LLM-powered systems in production, and experience deploying ML systems in cloud environments and operating them at scale.

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Key responsibilities include:

• Training state-of-the-art models, developed both internally and from the community, to deploy to our enterprise customers.
• Researching cutting-edge algorithms to integrate directly into our training stack.
• Building agents that leverage our proprietary agent-building algorithms to automatically hill climb datasets – including defining highly performant tools, multi-agent systems, and complex rewards.

Ideal candidates will have 1-3 years of building with LLMs in a production environment, experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO, and publications in top conferences such as NEURIPS, ICLR, or ICML within the last two years.

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training.

You’ll also receive benefits including comprehensive health, dental, and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

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Anthropic is seeking talented and experienced Software Engineers to join our Observability team within the Infrastructure organization. The Observability team owns the monitoring and telemetry infrastructure that every engineer and researcher at Anthropic depends on,from metrics and logging pipelines to distributed tracing, error analytics, alerting, and the dashboards and query interfaces that make it all actionable.

As Anthropic scales its infrastructure across massive GPU, TPU, and Trainium clusters, the volume and complexity of operational data is growing by orders of magnitude. We’re building next-generation observability systems,high-throughput ingest pipelines, cost-efficient columnar storage, unified query layers across signals, and agentic diagnostic tools,to ensure that engineers can detect, diagnose, and resolve issues in minutes rather than hours, even as the systems they operate become exponentially more complex.

Responsibilities

• Design and build scalable telemetry ingest and storage pipelines for metrics, logs, traces, and error data across Anthropic’s multi-cluster infrastructure

• Own and evolve core observability platforms, driving migrations and architectural improvements that improve reliability, reduce cost, and scale with organisational growth

• Build instrumentation libraries, SDKs, and integrations that make it easy for engineering teams to emit high-quality telemetry from their services

• Drive alerting and SLO infrastructure that enables teams to define, monitor, and respond to reliability targets with minimal noise

• Reduce mean time to detection and resolution by building cross-signal correlation, unified query interfaces, and AI-assisted diagnostic tooling

• Partner with Research, Inference, Product, and Infrastructure teams to ensure observability solutions meet the unique needs of each organisation

You May Be a Good Fit If You

• Have 10+ years of relevant industry experience building and operating large-scale observability or monitoring infrastructure

• Have deep experience with at least one observability signal area (metrics, logging, tracing, or error analytics) and familiarity with the others

• Understand high-throughput data pipelines, columnar storage engines, and the tradeoffs involved in ingesting and querying telemetry data at scale

• Have experience operating or building on top of observability platforms such as Prometheus, Grafana, ClickHouse, OpenTelemetry, or similar systems

• Have strong proficiency in at least one of Python, Rust, or Go

• Have excellent communication skills and enjoy partnering with internal teams to improve their operational visibility and incident response capabilities

• Are excited about building foundational infrastructure and are comfortable working independently on ambiguous, high-impact technical challenges

Strong Candidates May Also Have

• Experience operating metrics systems at very high cardinality (hundreds of millions of active time series or more)

• Experience with log storage migrations or operating columnar databases (ClickHouse, BigQuery, or similar) for analytics workloads

• Experience with OpenTelemetry instrumentation, collector pipelines, and tail-based sampling strategies

• Experience building or operating alerting platforms, on-call tooling, or SLO frameworks at scale

• Experience with Kubernetes-native monitoring, eBPF-based observability, or continuous profiling

• Interest in applying AI/LLMs to operational workflows such as automated root cause analysis, anomaly detection, or intelligent alerting

Logistics

• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

• Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

• Visa sponsorship: We do sponsor visas! However, we aren’t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact , advancing our long-term goals of steerable, trustworthy AI , rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We’re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.

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You will:

• Build synthetic data pipelines to generate enterprise environments to use for RL post-training
• Create agents to convert traces from production into actionable insights to use to improve agents
• Contribute to our agent building product which can construct other agents using coding agents + proprietary algorithms
• Train state-of-the-art models, developed both internally and from the community, to deploy to our enterprise customers

Ideally, you'd have:

• 3+ years of building with LLMs in a production environment
• Clear experiences with constructing high-quality data to use to improve an LLM/Agent
• Publications in top conferences such as NEURIPS, ICLR, or ICML within the last two years
• PhD or Masters in Computer Science or a related field

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training.

You'll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

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Your primary responsibility will be to lead conversation design and strategy for a multi-agent AI powered Pinterest Business Assistant to help business users (merchants, advertisers, and agencies) create inspired content, connect with customers, and achieve their business goals.

To succeed in this role, you'll need to act as the voice of the user by becoming an expert in our business products and leveraging research to inform the design of the AI assistant. You'll also drive improvements in prompt and skill management, owning the process from conception to production, and rapidly adapting to new technologies.

In addition to your technical skills, you'll need to be able to collaborate cross-functionally with researchers, product managers, engineers, and stakeholders to establish conversational, cohesive experiences with a unified voice. You'll apply systematic thinking to your work, contributing to scalable, consistent design patterns, and participating in critique to strengthen your designs.

As a Sr. Staff GenAI Content & Conversational Designer, you'll actively seek learning opportunities to grow your craft, define success metrics for novel AI features, and obsess over building trustworthy, high-impact AI systems.

We're looking for someone with a strong background in user-focused product conversation and content design, with experience shaping content for multi-disciplinary projects. You should have experience with LLMs, prompt shaping/engineering and working on AI product flows and with agentic systems. A portfolio demonstrating breadth and creativity and proven experience in content design, design thinking and product strategy is essential.

This position is not eligible for relocation assistance. You'll need to be in the office for in-person collaboration 1-2 times/quarter, and therefore can be situated anywhere in the country.

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Daily data-driven experiments will provide key insights around model strengths and inefficiencies which you'll use to improve your product's performance. You'll own, plan, and optimize the AI behind our Enterprise customer's deepest technical problems, leveraging our Scale Generative Platform (SGP) to build the most advanced AI agents across the industry.

Responsibilities:

• Own, plan, and optimize the AI behind our Enterprise customer's deepest technical problems
• Leverage SGP to build the most advanced AI agents across the industry including multimodal functionality, tool-calling, and more
• Have experience gathering business requirements and translating them into technical solutions
• Meet regularly with customer teams onsite and virtually, collaborating cross-functionally with all teams responsible for their data and ML needs
• Push production code in multiple development environments, writing and debugging code directly in both our customer's and Scale's codebases.

Ideal candidate will have a love for solving deeply complex technical problems with ambiguity using state of the art research and AI to accomplish your client's business goals, a strong engineering background, deep familiarity with a data-driven approach when iterating on machine learning models, and experience working with cloud technology stack and developing machine learning models in a cloud environment.

Nice to have: strong knowledge of software engineering best practices, experience building applications taking advantage of Generative AI in real, production use cases, and familiarity with state of the art LLMs and their strengths/weaknesses.

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Location: Dublin, Ireland

Department: Sales

Job Description:

Intercom is the AI Customer Service company on a mission to help businesses provide incredible customer experiences. Our AI agent Fin, the most advanced customer service AI agent on the market, lets businesses deliver always-on, impeccable customer service and ultimately transform their customer experiences for the better.

Fin can also be combined with our Helpdesk to become a complete solution called the Intercom Customer Service Suite, which provides AI enhanced support for the more complex or high touch queries that require a human agent.

Founded in 2011 and trusted by nearly 30,000 global businesses, Intercom is setting the new standard for customer service.

Driven by our core values, we push boundaries, build with speed and intensity, and consistently deliver incredible value to our customers.

What's the opportunity?

Intercom's Global Sales Organization is rapidly evolving, and the GTM Enablement team is expanding to support. In this critical new role, you will solve the "Last Mile" gap in technical readiness, serving as the bridge between R&D, Product, and our customer-facing Solutions teams.

As the Senior Product Enablement Manager (Solutions), you will act as the single-threaded owner of the technical education strategy for our Solutions organization (CSMs, SEs, and Professional Services).

You will be responsible for translating our rapid product innovation and AI capabilities into clear, scalable enablement that accelerates adoption and strengthens customer outcomes.

This role is distinct from GTM Strategy; while they architect the commercial plan, you will own the early-stage positioning, solutions readiness, and technical fluency required to ensure our teams understand how our products work and how to deliver them effectively.

What will I be doing?

Reporting to the GTM Enablement leadership, you will partner directly with R&D and Product Management to build and deliver a comprehensive technical enablement program.

Technical Education Strategy & Curriculum - Developing a scalable and repeatable strategy for the technical education of AEs, RMs, CSMs, SEs, and Professional Services.

Creating and maintaining a full suite of technical training materials, including hands-on labs, documentation, and how-to guides.

Leading and facilitating technical training sessions, both live and on-demand, including "Train the Trainer" programs and new product release training.

AI Fluency & Certification - Owning the AI Fluency Program, creating a unified baseline of understanding regarding our AI capabilities (Fin) across the GTM organization.

Building and operationalizing a scalable certification framework that integrates AI learning objectives and continuous upskilling into onboarding and ongoing enablement.

Ensuring every GTM role is fluent in AI and able to guide customers through AI-driven change management and adoption.

Cross-Functional Partnership (R&D Bridge) - Serving as the primary liaison between R&D and the Solutions teams, translating product functionality and architecture into digestible, actionable training content.

Acting as the primary conduit for feedback from the Solutions teams back to R&D and Product, synthesizing field insights to help inform the product roadmap.

What skills do I need?

• 5+ years in Sales Enablement, Solutions Engineering, Technical Training, or a related role in a SaaS organization.

A strong technical aptitude with the ability to bridge R&D and GTM, translating complex technical details into clear guidance for customer-facing teams.

Experience designing and delivering technical curriculum, including hands-on labs, certifications, and self-paced learning interventions.

Deep understanding of the "Solutions" function (CSMs, SEs, Professional Services) and the technical readiness required to drive customer adoption and retention.

The ability to work cross-functionally and build trusted relationships with Product Managers, R&D, and GTM leadership.

Excellent communication and presentation skills, with an intuitive sense for delivering the right technical information at the right time.

Analytical mindset with the ability to measure technical proficiency and report on the effectiveness of certification programs

Bonus skills & attributes

• Experience at a high-growth SaaS company.

Familiarity with AI technology and experience enabling teams on AI-driven products.

Background in instructional design or technical writing.

Experience using tools like Salesforce, Gong, or modern LMS platforms (e.g., Workramp, Highspot).

Experience working in a globally distributed team.

Benefits

We are a well-treated bunch, with awesome benefits! If there’s something important to you that’s not on this list, talk to us!

• Competitive salary and equity in a fast-growing start-up

We serve lunch every weekday, plus a variety of snack foods and a fully stocked kitchen

Regular compensation reviews - we reward great work!

Pension scheme & match up to 4%

Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents

Flexible paid time off policy

Paid maternity leave, as well as 6 weeks paternity leave for fathers, to let you spend valuable time with your loved ones

If you’re cycling, we’ve got you covered on the Cycle-to-Work Scheme. With secure bike storage too

MacBooks are our standard, but we also offer Windows for certain roles when needed.

#LI-Hybrid

Policies

Intercom has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week.

We have a radically open and accepting culture at Intercom. We avoid spending time on divisive subjects to foster a safe and cohesive work environment for everyone.

As an organization, our policy is to not advocate on behalf of the company or our employees on any social or political topics out of our internal or external communications.

We respect personal opinion and expression on these topics on personal social platforms on personal time, and do not challenge or confront anyone for their views on non-work related topics.

Our goal is to focus on doing incredible work to achieve our goals and unite the company through our core values.

Intercom values diversity and is committed to a policy of Equal Employment Opportunity. Intercom will not discriminate against an applicant or employee on the basis of race, color, religion, creed, national origin, ancestry, sex, gender, age, physical or mental disability, veteran or military status, genetic information, sexual orientation, gender identity, gender expression, marital status, or any other legally recognized protected basis under federal, state, or local law.

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The Insider Risk Team works cross-functionally to deter, identify, investigate and mitigate risks to Anthropic's most critical assets,our people, our data, and our infrastructure.

Responsibilities:

• Triage custom technical detection alerts
• Independently conduct end-to-end insider risk investigations while working closely with IT, Detection and Response, Legal, HR and other cross-functional teams
• Monitor and triage external threats targeting employees
• Conduct sensitive interviews of employees or other involved parties
• Perform technical analysis of logs from SIEM, DLP, UEBA systems
• Leverage AI tools (Claude, Claude Code) to accelerate investigation workflows and data analysis
• Build and maintain investigation documentation
• Assist in iterating and improving on processes, procedures and systems to detect, mitigate and investigate insider risks
• Work cross-functionally to develop, refine and operationalize insider risk indicators, scenarios and mitigation strategies
• Provide rapid-turnaround security assessments to support business operations
• Support education and awareness programs to promote a robust security culture
• Serve as the subject matter expert for insider risk and provide training to team members as needed

You may be a good fit if you have:

• Bachelor's degree and/or higher education in a related field
• 5-8 years of experience in insider risk, corporate investigations or a related domain
• 3-5 years experience in conducting investigative interviews
• Experience conducting OSINT for threat assessment, or counterintelligence
• Experience leveraging DLP, UEBA, SIEM, SOAR and other insider risk security tooling for detections and investigations
• Broad understanding of internal and external investigations, cybersecurity, interview techniques, risk assessment and managing strong cross-functional relationships
• Ability to communicate complex security findings clearly and concisely to non-technical stakeholders (written and verbal)
• Track record of rapid response to time-sensitive security requests
• Comfort operating across organizational boundaries (Security, People, Legal, IT)
• Exceptional communication, collaboration skills and the ability to lead projects with little guidance
• Demonstrated ability to operate independently with minimal oversight while managing sensitive cases

Strong candidates may also have:

• Experience working in the technology industry or at/with AI/ML companies
• Experience with counterintelligence investigations and nation-state threat actor TTPs
• Background in open-source intelligence collection and analysis
• Track record of AI/LLM adoption for productivity gains in investigative work
• Experience contributing to a high growth startup environment
• Specialized knowledge of risks unique to the AI sector
• Experience with data exfiltration investigations across multiple vectors (email, cloud, removable media)
• Experience working in government, defense, or high-security environments

What makes you successful here:

• Entrepreneurial mindset: You see gaps and fill them without being asked
• Technical + human balance: Equal comfort analyzing log data and conducting sensitive interviews
• AI-native approach: You leverage LLMs to work smarter, not just harder
• Mission alignment: You understand AI safety stakes and insider risk's role in protecting that mission
• Judgment under uncertainty: You make sound decisions with incomplete information
• Clear communicator: You distill complex findings into actionable insights for diverse audiences
• Cross-functional navigator: You build relationships and collaborate effectively across teams

Annual compensation range for this role is $245,000-$305,000 USD.

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You'll work with enterprise clients to understand their unique challenges, lead a team that architects specific AI solutions, and ensure successful deployment and adoption of AI systems in production environments.

This is a Management role that combines deep engineering and AI expertise, leading a team, and working on customer-facing problems. You'll work directly with customer engineering teams to integrate AI into their critical workflows.

Customer Integration & Deployment

Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements.

Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs).

Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows.

Deploy and configure AI models and agents within customer security and compliance boundaries.

AI Agent Development

Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation.

Architect multi-agent systems that orchestrate between different models, tools, and data sources.

Implement evaluation frameworks to measure agent performance and iterate toward business objectives.

Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement.

Prompt Engineering & Optimization

Create sophisticated prompt engineering strategies optimized for customer-specific domains and data.

Build and maintain prompt libraries, templates, and best practices for customer use cases.

Conduct systematic prompt experimentation and A/B testing to improve model outputs.

Implement RAG (Retrieval Augmented Generation) systems and fine-tuning pipelines where appropriate.

Leadership & Collaboration

Serve as the Engineering Manager and technical point of contact for strategic enterprise accounts.

Lead a team that is collaborating with customer data scientists, ML engineers, and software developers to ensure smooth integration.

Work closely with Scale's product and engineering teams to translate customer needs into product improvements.

Document technical architectures, integration patterns, and best practices.

Problem Solving & Innovation

Debug complex technical issues across the entire stack, from data pipelines to model outputs.

Rapidly prototype solutions to unblock customers and prove out new use cases.

Stay current on the latest AI/ML research and tools, bringing innovative approaches to customer problems.

Identify opportunities for productization based on common customer patterns.

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At Cresta, shipping AI is only half the story. Ensuring that AI interacts with humans reliably, accurately, and empathetically at scale is where the real challenge lies. As the QA Lead, AI Agent, you will be the ultimate guardian of the customer experience for our AI Agent product line. This role is perfect for a strategic quality expert who loves the intersection of human psychology and machine logic.

You will own the end-to-end quality strategy, from designing complex test plans for non-deterministic LLMs to building automated and scalable testing environments using Cresta's proprietary no-code test and evaluation tools. You aren't just looking for bugs; you are building the framework that allows Cresta to deploy world-class AI agents for the world's largest enterprises with total confidence.

Responsibilities

• Architect & Scale AI Evaluation Systems: Design and oversee the end-to-end framework for testing AI agent systems at scale. You will leverage LLM-driven methodologies,including automated simulations, "LLM-on-LLM" rubrics, and adversarial red-teaming,to ensure reliability, policy adherence, and logic across complex, multi-turn conversational flows.

• Drive Deployment Excellence: Partner with Forward Deployed Engineers and PMs to triage issues, identify bottlenecks, and create new test cases on the fly to address real-world deployment challenges.

• Be the Customer’s Voice: Conduct manual UAT and voice-call testing to represent the end-customer experience. You take it personally when an agent lacks empathy or clarity, and you excel at articulating these nuances to the engineering team and clients.

• Lead and Scale the Team: lead a pod of QA analysts and partners. You will define the best practices, communication loops, and shared knowledge base that allow the QA function to scale alongside our rapidly growing product line.

Requirements

• 5+ years of experience in Quality Engineering, Deployments, or Technical QA, ideally within an AI or high-growth SaaS environment.

• Systems Thinking: A strong technical intuition and curiosity about how LLMs work. While you don't need to code, you must be comfortable navigating technical concepts like LLM, RAG, prompt logic, and multi-turn conversational flows.

• Operational Leadership: Proven ability to large E2E technical projects through partners, and a passion for building processes that improve efficiency between QA, Engineering, and Product.

• The "QA Nose": An uncanny ability to find the edge case and a bias toward action. You anticipate bottlenecks before they happen and deliver solutions with urgency.

• High Empathy: A consultative mindset with the ability to represent the "human element" of a customer support interaction.

• Startup Agility: You thrive in fast-paced environments, excel at turning ambiguity into execution, and are comfortable "rolling up your sleeves" to build.

Bonus Points

• Experience with CCaaS (Contact Center as a Service), telephony, or STT/TTS (Speech-to-Text) technologies.

• Background in Conversation Design or SDET roles.

• Experience leading team with direct reports.

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Responsibilities:

• Inspire, lead, and grow a team of data scientists to achieve our longer-term vision
• Drive data science projects end-to-end in partnership with Product, Engineering, and other partners to inform product strategy and investment decisions
• Analyze large datasets to identify trends, patterns, and insights that can help understand marketplace dynamics and help cross-functional teams (e.g., product, engineering, marketing) to define and execute data-driven optimization strategies
• Actively influence the design of the strategy and shaping of the roadmap. Generate and use team insights to set and prioritise longer-term goals
• Create and implement A/B testing, experimentation, and other cutting-edge statistical/mathematical frameworks to analyse Ads (marketplace) performance
• Continually develop & execute on a Data Science roadmap and vision for your team
• Stay abreast of industry best practices and emerging technologies in the field of advertising and data science
• Foster a culture of innovation, collaboration, and technical excellence
• Be an integral part of the Data Science Org, leveraging and contributing to the vibrant knowledge base, shared across a community of world-class data experts

Required Qualifications:

• PhD or Master's degree in Economics, Statistics, Machine Learning, Operations Research, or other quantitative fields
• 4+ years of management experience. Experience managing managers is a bonus
• Strong skills in programming (Python or R) and SQL
• Experience in leveraging AI-assisted development tools (e.g., Cursor, Claude, or similar LLMs) to improve personal and team productivity, code quality, and technical problem-solving
• Deep understanding of Ads Marketplace
• Extensive experience of online experimentation and causal inference
• Ability to communicate & discuss low-level technical topics as well as high-level strategies
• Comfortable in innovative and fast-paced environments, and an innate ability to bias toward action
• Results-oriented with a strong customer and business focus
• Track-record driving product roadmap and execution with strong cross-org collaborations
• Ability to provide structure and tackle ambiguous and undefined problems

Benefits:

• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Comprehensive Medical Benefits & Health Care Spending Account
• Registered Retirement Savings Plan with matching contributions
• Income Replacement Programs
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave

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Daily data-driven experiments will provide key insights around model strengths and inefficiencies which you'll use to improve your product's performance. You'll own, plan, and optimize the AI behind our Enterprise customer's deepest technical problems, leveraging our Scale Generative Platform (SGP) to build the most advanced AI agents across the industry.

Responsibilities:

• Own, plan, and optimize the AI behind our Enterprise customer's deepest technical problems
• Leverage SGP to build the most advanced AI agents across the industry, including multimodal functionality, tool-calling, and more
• Have experience gathering business requirements and translating them into technical solutions
• Meet regularly with customer teams onsite and virtually, collaborating cross-functionally with all teams responsible for their data and ML needs
• Push production code in multiple development environments, writing and debugging code directly in both our customer's and Scale's codebases

Ideally, you'd have:

• A love for solving deeply complex technical problems with ambiguity using state of the art research and AI to accomplish your client's business goals
• Strong engineering background: a Bachelor’s degree in Computer Science, Mathematics, or another quantitative field or equivalent strong engineering background
• Deep familiarity with a data-driven approach when iterating on machine learning models and how changes in datasets can influence model results
• Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment
• Proficiency in Python to write, test and debug code using common libraries (ie numpy, pandas)

Nice to haves:

• Strong knowledge of software engineering best practices
• Have built applications taking advantage of Generative AI in real, production use cases
• Familiarity with state of the art LLMs and their strengths/weaknesses

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You will contribute to exploratory experimental research on AI safety, with a focus on risks from powerful future systems. As a Research Engineer on Alignment Science, you'll work on creating methods to ensure advanced AI systems remain safe and harmless in unfamiliar or adversarial scenarios.

Responsibilities:

• Conduct research on AI control and alignment stress-testing
• Develop and implement new techniques for ensuring AI safety
• Collaborate with other teams, including Interpretability, Fine-Tuning, and the Frontier Red Team
• Test and evaluate the effectiveness of AI safety techniques

Requirements:

• Significant software, ML, or research engineering experience
• Familiarity with technical AI safety research
• Experience contributing to empirical AI research projects

Preferred qualifications:

• Experience authoring research papers in machine learning, NLP, or AI safety
• Experience with LLMs
• Experience with reinforcement learning

Benefits:

• Competitive compensation and benefits
• Optional equity donation matching
• Generous vacation and parental leave
• Flexible working hours

Note:

This role requires all candidates to be based at least 25% in London and travel to San Francisco occasionally.

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You'll design, adapt, and deliver enablement programs that accelerate pipeline growth, increase average deal size, and help sellers build long-term careers at Reddit.

Responsibilities:

Represent the SMB Seller: Partner with SMB vendor and sales teams to ensure third-party sellers are equipped with the same playbooks, messaging, and workflows to drive consistent execution and performance across all regions.

Enable Pipeline Generation: Develop playbooks, messaging, and outreach frameworks that help sellers generate qualified pipeline through targeted prospecting and effective early-stage conversations.

Drive Seller Productivity at Scale: Equip reps with simple, repeatable workflows and resources that help them manage high activity volumes, prioritize accounts, and move opportunities forward efficiently.

Accelerate Ramp & Execution: Support onboarding and ongoing development programs that help new sellers ramp quickly and existing sellers continuously improve performance.

Operationalize GTM Programs: Adapt global enablement initiatives including tooling rollouts, sales plays, and AI-assisted selling to fit the pace and workflow of SMB teams.

Use Data to Improve Performance: Track enablement effectiveness through metrics like ramp time, pipeline generation, meeting conversion rates, and deal velocity, iterating programs based on results.

Connect the Revenue Ecosystem: Partner with Sales, Marketing, Product, and Revenue Operations to ensure alignment across messaging, tools, and programs that drive SMB growth.

Qualifications:

8-10+ years in sales enablement, sales operations, or sales leadership,experience in SMB or commercial segments required

Experience designing and running enablement programs for third-party or vendor sales teams, ensuring consistent standards, messaging, and performance expectations.

Exceptional facilitator and communicator with strong stakeholder management skills.

Data-driven and fluent in using metrics, dashboards, and AI-powered insights to diagnose needs and evaluate outcomes.

Proficient in enablement tools (Highspot, Gong, LMS), Salesforce, and analytics platforms.

Committed to inclusive, accessible learning design that meets diverse seller needs.

Benefits:

Comprehensive Healthcare Benefits and Income Replacement Programs

401k with Employer Match

Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support

Family Planning Support

Gender-Affirming Care

Mental Health & Coaching Benefits

Flexible Vacation & Paid Volunteer Time Off

Generous Paid Parental Leave

Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission.

Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave.

To learn more, please visit https://www.redditinc.com/careers/

To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state.

We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies.

Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.

The base salary range for this position is: $143,600-$201,000 USD

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Key Responsibilities:

• Build AI-Native Tooling: Move beyond traditional automation by implementing AI-driven agents that optimize our CI/CD pipelines and provide intelligent feedback to developers.
• Enhance Developer Velocity: Identify and resolve systemic bottlenecks in the development lifecycle, allowing teams to move faster without compromising quality.
• Advocate for Quality by Design: Work directly with product teams to guide architectural decisions, ensuring that new features are modular and testable from the first line of code.
• Ship High-Scale Infrastructure: Own the development and maintenance of frameworks used by hundreds of engineers across Airbnb, ensuring they are performant, reliable, and easy to use.

A Typical Day:

• Hands-on Development: Write high-quality, performant Kotlin code to extend testing frameworks and build AI-powered developer tools, leveraging LLMs to accelerate development workflows.
• Technical Ownership: Take ownership of key components of our Automated Quality Platform, ensuring operational excellence and high availability (24x7) of our testing infrastructure.
• Design & Review: Participate in deep-dive design reviews for new Android features, providing expert guidance on modularity and testability patterns.
• Applied AI: Implement LLM-based solutions for smart test orchestration, test case generation, and autonomous test discovery to reduce CI feedback loops.
• Cross-Functional Collaboration: Partner with Product and Mobile Infrastructure teams to align platform capabilities with the needs of the broader engineering org.
• Mentorship: Review code and provide technical guidance to peers, fostering a culture of commitment to craft and engineering rigor.

Your Expertise:

• Experience: 3+ years of professional Android development experience (or with a PhD) in a fast-paced, high-growth tech environment.
• Technical Mastery: Strong proficiency in Kotlin and the Android SDK. You have a solid understanding of modern Android architecture and the Gradle build lifecycle.
• Infrastructure Experience: Demonstrated expertise in building or maintaining test automation frameworks (e.g., Espresso, Compose Test) at scale.
• CI/CD & Tools: Familiarity with CI/CD orchestration and a passion for building tools that improve the developer experience.
• AI Curiosity: A strong interest or hands-on experience in leveraging AI/LLMs to solve engineering productivity or quality challenges.
• Problem Solving: Proven ability to navigate complex, ambiguous codebases and implement best-in-class solutions.
• Communication: Excellent communication skills with the ability to facilitate technical discussions across cross-functional teams.

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You are a Systems Engineer at heart, but you are ready to apply LLMs, RAG, and predictive modeling to solve infrastructure challenges at scale.

Our Team's Stack:

• Languages: Python, Go, bash/sh
• Observability: Prometheus, Victoria Metrics, Grafana
• OS & Kernel: Linux Kernel (custom build), Ubuntu
• Hardware: Intel/AMD/ARM CPUs, Nvidia GPUs, DPUs, Infiniband and Ethernet NICs
• Containerization: Docker, Kubernetes (k8s), KubeVirt, containerd, kubelet

Responsibilities:

• Pipeline Architecture: Design, maintain, and automate reproducible OS image build pipelines for our massive fleet of GPU-accelerated servers.
• Kernel Distribution: Collaborate with kernel engineers to package, validate, and distribute custom Linux builds across Intel, AMD, and ARM architectures.
• Dependency Management: Build tooling to manage dependencies, versioning, and release workflows, ensuring hermetic builds.
• Telemetry & Metrics: Standardize the collection of build metrics to create a baseline for future AI modeling.
• 'Smart' CI/CD & Auto-Remediation: Architect AI agents that ingest and analyze build logs in real-time. Develop systems that auto-triage errors, categorize failure patterns, and generate context-aware fix suggestions for engineering teams.
• Predictive Regression Modeling: Design ML workflows that utilize historical performance data to detect kernel and OS regressions (latency, throughput, stability) in staging environments before they impact production.
• Dynamic Kernel Tuning: Implement closed-loop feedback systems that analyze real-time system metrics and automatically suggest or apply sysctl parameter optimizations for specific customer workloads.
• Next-Gen ChatOps: Engineer LLM-driven interfaces for Slack/internal tools, enabling stakeholders to query build statuses, request log summaries, or provision resources using natural language commands.

Requirements:

• 4+ years of professional experience in Linux Systems Engineering, Release Engineering, or DevOps.
• Deep knowledge of Linux internals (boot process, kernel modules, networking stack).
• Experience with package management (Debian/Ubuntu) and build systems.
• Strong proficiency in Python (essential for the AI integration aspects of this role).
• Demonstrable experience integrating API-based AI models (OpenAI, Anthropic, or local open-source models) into software workflows.
• Understanding of RAG (Retrieval-Augmented Generation) architectures for querying technical documentation or logs.
• Experience building event-driven automation (e.g., using webhooks to trigger analysis agents).
• Familiarity with data structures required for vector search or time-series analysis.

Nice-to-haves:

• Experience with Kubeflow or MLFlow.
• Background in High-Performance Computing (HPC).
• Experience fine-tuning small language models (SLMs) for code or log analysis tasks.

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Responsibilities:

• Design, develop, and deploy Cresta's AI Agent solutions and proprietary models.
• Focus on practical AI challenges such as improving reasoning, planning capabilities, and evaluation in real-world scenarios.
• Collaborate with cross-functional teams including front-end and back-end software engineers to integrate AI Agents into Cresta's customer solutions.
• Lead initiatives to scale AI systems for production environments, ensuring performance and reliability across use cases.
• Contribute to solving cutting-edge problems in AI and help define the future roadmap for Cresta's AI Agents.
• Innovate and research ways to improve security, cost-efficiency, and reliability of AI systems.

Qualifications:

• Bachelor's or Master's Degree in Computer Science, Mathematics, or a related field.
• 2+ years of hands-on industry experience with AI and machine learning, preferably with experience working with LLMs in large-scale production environments.
• Solid knowledge of machine learning concepts and methods, especially those related to NLP, Generative AI, and working with LLMs.
• Practical knowledge of modern machine learning frameworks and technologies (e.g., PyTorch, Tensorflow, Hugging Face, NumPy), as well as experience with distributed systems and cloud-based AI infrastructure.
• Strong problem-solving and strategic thinking abilities, with a proven ability to lead cross-functional teams and work collaboratively to deliver innovative AI solutions in production.
• A passion for driving AI adoption and pushing the boundaries of AI technology into real-world applications, with an ability to mentor junior engineers and influence strategic decisions across the organization.

Perks & Benefits:

• We offer Cresta employees a variety of medical, dental, and vision plans, designed to fit you and your family's needs.
• Paid parental leave to support you and your family.
• Monthly Health & Wellness allowance.
• Work from home office stipend to help you succeed in a remote environment.
• Lunch reimbursement for in-office employees.
• PTO: 3 weeks in Canada.

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Solve distributed systems problems: Own session management across scaled-out workers , including affinity, checkpointing, crash recovery, and consistency under concurrent access.

Build a function execution platform: Own a serverless-style runtime where customers deploy custom logic , build orchestration, container lifecycle, autoscaling, and versioned rollouts.

Own developer experience and test infrastructure: Build CLI tools, local development environments, and test execution frameworks that let engineers iterate quickly and ship with confidence.

Raise the bar on production quality: Drive observability, incident response, and engineering best practices across the team.

We're looking for a senior software engineer with 5+ years of experience in infrastructure, platform, or systems work. You should have strong Python and Go skills, as well as a deep understanding of distributed systems, consistency, fault tolerance, state management, and concurrency.

Experience with Kubernetes and cloud-native infrastructure is also required. You should be able to build developer-facing tooling, such as CLIs, SDKs, local dev environments, or internal platforms.

A high bar for code quality, thorough testing, thoughtful code review, and sustainable engineering practices are essential. You should be comfortable operating what you build, on-call, incident response, and production ownership.

AI-native workflow is a must, and you should actively use LLMs and AI-assisted tools in your daily development.

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Anthropic's Product Engineering org is looking for experienced engineers with strong full-stack fundamentals to join one of teams owning our current or emergent products. You'll be a technical leader who thinks holistically about the consumer and/or enterprise end user experience - be that via Claude.ai, the Anthropic API, enterprise deployments, Claude Code, or mission-driven applications - and carry real end-to-end ownership.

You'll partner with engineering managers, product leaders, designers, and researchers to understand new model capabilities and redefine what is possible for users in the world of LLMs - and how to build it. We’ll look to you to have a product-oriented mindset and input, own technical quality across the stack (performance, accessibility, reliability, and developer experience), scale your efforts to millions of users on a global scale, and carry genuine excitement about what AI makes possible.

We have multiple teams that are currently hiring. Team placement occurs after the interview process, taking into account your interests and experience alongside organisational needs. This flexible approach allows us to match talented engineers with the backend product efforts where they'll have the greatest impact and growth potential.

Developer Experience

You'll build the products and tools - console, SDKs, docs, and observability - that give developers the confidence to rely on Claude in their most critical applications. Our mission is to meet developers where they are and bring them closer to the ceiling of what's possible with our models and API. That means building trust through great platform fundamentals, inspiring developers to raise the bar in how they use Claude's capabilities, and accelerating the path to agentic development by designing for both human and AI developers.

You'll work closely with teams across the Platform org to turn Claude's newest capabilities into experiences developers can actually pick up and run with - from first prompt to production agent.

Beneficial Deployments

Beneficial Deployments Engineering brings Claude to organisations doing the most good with the fewest resources , nonprofits, schools, healthcare providers, researchers, and economic mobility programs.

Enterprise AI Products

You'll work on the products that make Claude a daily-use tool for enterprise customers across industries – the connective tissue that lets Claude operate effectively across workflows. On this team you will systematically understand why Enterprise users aren't activating, what's blocking adoption, and building the capabilities to close those gaps.

Some of our focuses are:

• Extensibility , plugins, skills, connectors, and the MCP ecosystem that lets a company shape Claude around their specific workflows and distribute that work across teams.

• Context , enterprise knowledge, organisational memory, and the retrieval layer that makes Claude genuinely aware of a company's people, documents, and workflows. A connected, contextual Claude is the difference between a general-purpose chatbot and a real coworker.

• Proactivity , Cowork suggestions, workflow capture, ambient Claude inside the apps people already use. Moving from 'Claude answers when asked' to 'Claude notices what you need'.

Vertical AI Products

Purpose-built experiences for specific industries where Claude can transform complex professional work. We're currently building for three verticals, with more to come:

• Financial Services , analysts and bankers building models, memos, and decks under deadline. We're building retrieval, analysis, and document generation that holds up to executive review.

• Healthcare , clinical documentation, prior auth, and care coordination. Work where accuracy isn't a feature, it's the whole product , and where compliance is part of the engineering.

• Legal , contract analysis, document review, and matter management for teams that will read every word we generate and know immediately if it's wrong.

Enterprise Foundations

You'll build the systems large organisations require before they can adopt Claude at scale: identity and permissions, security and compliance controls, and the admin analytics that let them see how it's being used. This is the work that turns 'we love the demo' into a signed enterprise deal. The role is part product, part platform. You'll work closely with Product and GTM to understand what our largest customers need, then build it once in a way that works across Claude.ai, Claude Code, and Cowork.

Growth

Drive user acquisition, engagement, retention, and monetisation through data-driven strategies and technical implementations. At Anthropic, we're not just building AI tools; we're reimagining how AI can enhance and expand its user base!

As a member of the growth team, you will have a unique opportunity to shape our growth strategy. You will work with a cross-functional team of engineers, data scientists, marketers, and product managers to design, implement, and optimise growth initiatives that scale our AI-powered tools and maximise their impact.

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At Coinbase, our mission is to increase economic freedom in the world.

We're seeking a Senior Staff Software Engineer, Backend - Platform (Core Automation) to join our team.

As a member of our Core Automation team, you will be responsible for designing and implementing Agentic AI systems that power Coinbase’s customer support experience and compliance processes.

You will also design a platform (primitives, orchestration platform, tools, etc.) that would allow other domains to quickly leverage Agentic AI to automate their processes.

Interacting with stakeholders in many different organizations that build Coinbase products or are responsible for financial operations is also a key part of this role.

Participating in shaping of the strategy and execution path of Coinbase Platform is another important responsibility.

You will manage individual projects priorities, deadlines and deliverables with your technical expertise.

Mentoring and training other team members on design techniques and coding standards is also a key aspect of this role.

Writing high quality, well tested code to meet the needs of your customers is essential.

What we look for in you:

12 + years of experience in backend software engineering using Golang or similar languages

Experience getting LLM based application to production

Proven track record of delivering impactful solutions that power significant customer flows and processes

You’ve experience in architecting and developing solutions to ambiguous problems with significant impact

Strong technical knowledge of building distributed systems that process massive scale

Solid communication skills and ability to communicate to stakeholders with various technical and non-technical backgrounds

Relentless drive to set and perseverance to achieve ambitious goals

Passion for building an open financial system that brings the world together

Demonstrates the ability to responsibly use generative AI tools and copilots (e.g., LibreChat, Gemini, Glean) in daily workflows, continuously learn as tools evolve, and apply human-in-the-loop practices to deliver business-ready outputs and drive measurable improvements in efficiency, cost, and quality.

Nice to haves:

Experience with LLM and Agentic AI

Measuring and improving LLMs’ grounding to a given corpus and experience reducing hallucinations is a big plus

Experience in the customer support, compliance or financial crimes domains

Experience having made build/buy decisions

Job #: P72990

Pay Transparency Notice: Depending on your work location, the target annual base salary for this position can range as detailed below.

Total compensation may also include equity and bonus eligibility and benefits (including medical, dental, vision and 401(k)).

Annual base salary range (excluding equity and bonus):

$253,895-$298,700 USD

Please be advised that each candidate may submit a maximum of four applications within any 30-day period.

We encourage you to carefully evaluate how your skills and interests align with Coinbase's roles before applying.

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Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence.

The Role

In this role, you'll work with a team of elite researchers and engineers to design and implement post-training strategies that enhance Gemini’s capabilities in code security analysis. You will bring contributions to our ML innovation, post-training refinement (SFT/RLHF), advanced evaluation, and data generation to ensure our models can reliably perform safe and powerful code security analysis.

Key responsibilities:

• Design and Implement advanced post-training algorithms (SFT, RLHF, RLAIF) to optimize Gemini for code security tasks and secure coding practices.

• Diagnose and interpret training outcomes (regressions in coding ability, gains in security reasoning), and propose solutions to improve model capabilities.

• Actively monitor and evolve the system's performance through metric design.

• Develop reliable automated evaluation pipelines for code security that are strongly correlated with human security expert judgment.

• Construct complex benchmarks to probe the limits of the model’s ability to reason about control flow, memory safety, and software weakness.

About You

We are seeking individuals who excel in fast-pacing environments and are eager to contribute to the advancement of AI. We highly value the ability to invent novel solutions to complex problems, embracing a can-do and fail-fast mindset. We are looking for someone who genuinely believes in the future of AI and is committed to devoting their energy in this field.

In order to set you up for success as a Research Engineer at Google DeepMind, we look for the following skills and experience:

• BSc, MSc or PhD/DPhil degree in computer science, stats, machine learning or similar experience working in industry

• Deep understanding of statistics is strongly preferred

• Experiences in fine-tuning and adaptation of LLMs (e.g. advanced prompting, supervised fine-tuning, RLHF)

• Strong knowledge of systems design and data structures

• Proven experience with TensorFlow, JAX, PyTorch, or similar leading deep learning frameworks

• Recent experience conducting applied research to improve the quality and training/serving efficiency of large transformer-based models

• A passion for Artificial Intelligence.

• Excellent communication skills and proven interpersonal skills, with a track record of effective collaboration with cross-functional teams

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Anthropic is seeking talented and experienced Software Engineers to join our Observability team within the Infrastructure organization. The Observability team owns the monitoring and telemetry infrastructure that every engineer and researcher at Anthropic depends on,from metrics and logging pipelines to distributed tracing, error analytics, alerting, and the dashboards and query interfaces that make it all actionable.

By joining this team, you’ll have a direct impact on the reliability and operational excellence of Anthropic’s research and product systems.

As Anthropic scales its infrastructure across massive GPU, TPU, and Trainium clusters, the volume and complexity of operational data is growing by orders of magnitude. We’re building next-generation observability systems,high-throughput ingest pipelines, cost-efficient columnar storage, unified query layers across signals, and agentic diagnostic tools,to ensure that engineers can detect, diagnose, and resolve issues in minutes rather than hours, even as the systems they operate become exponentially more complex.

Responsibilities

• Design and build scalable telemetry ingest and storage pipelines for metrics, logs, traces, and error data across Anthropic’s multi-cluster infrastructure

• Own and evolve core observability platforms, driving migrations and architectural improvements that improve reliability, reduce cost, and scale with organisational growth

• Build instrumentation libraries, SDKs, and integrations that make it easy for engineering teams to emit high-quality telemetry from their services

• Drive alerting and SLO infrastructure that enables teams to define, monitor, and respond to reliability targets with minimal noise

• Reduce mean time to detection and resolution by building cross-signal correlation, unified query interfaces, and AI-assisted diagnostic tooling

• Partner with Research, Inference, Product, and Infrastructure teams to ensure observability solutions meet the unique needs of each organisation

You May Be a Good Fit If You

• Have 10+ years of relevant industry experience building and operating large-scale observability or monitoring infrastructure

• Have deep experience with at least one observability signal area (metrics, logging, tracing, or error analytics) and familiarity with the others

• Understand high-throughput data pipelines, columnar storage engines, and the tradeoffs involved in ingesting and querying telemetry data at scale

• Have experience operating or building on top of observability platforms such as Prometheus, Grafana, ClickHouse, OpenTelemetry, or similar systems

• Have strong proficiency in at least one of Python, Rust, or Go

• Have excellent communication skills and enjoy partnering with internal teams to improve their operational visibility and incident response capabilities

• Are excited about building foundational infrastructure and are comfortable working independently on ambiguous, high-impact technical challenges

Strong Candidates May Also Have

• Experience operating metrics systems at very high cardinality (hundreds of millions of active time series or more)

• Experience with log storage migrations or operating columnar databases (ClickHouse, BigQuery, or similar) for analytics workloads

• Experience with OpenTelemetry instrumentation, collector pipelines, and tail-based sampling strategies

• Experience building or operating alerting platforms, on-call tooling, or SLO frameworks at scale

• Experience with Kubernetes-native monitoring, eBPF-based observability, or continuous profiling

• Interest in applying AI/LLMs to operational workflows such as automated root cause analysis, anomaly detection, or intelligent alerting

Logistics

• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

• Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

• Visa sponsorship: We do sponsor visas! However, we aren’t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

How we’re different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact , advancing our long-term goals of steerable, trustworthy AI , rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We’re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.

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As one of the first pioneers of earned wage access, our focus at EarnIn is building products that deliver real-time financial flexibility for those with unique needs.

We're fortunate to have an experienced leadership team and world-class funding partners. We're growing fast and are excited to bring world-class talent onboard to help shape the next chapter of our growth journey.

Position Summary

We're looking for a Staff Backend Engineer to join the Core Services team at EarnIn. We're seeking experienced, passionate, and resourceful engineers to join our backend teams.

This position will be hybrid from our Bengaluru office, with 2+ days in the office. EarnIn provides excellent employee benefits, including healthcare, internet/cell phone reimbursement, a learning and development stipend, and opportunities to collaborate with and travel to our Mountain View HQ and Bangkok Site.

Responsibilities

• Design and implement scalable, high-quality backend features and REST APIs
• Drive end-to-end execution of complex initiatives, from design to production
• Maintain and extend test automation to support CI/CD
• Mentor engineers and provide guidance through code and architecture reviews
• Collaborate with cross-functional teams (Product, Design, Data Science, Marketing)
• Debug and resolve production issues across services and infrastructure
• Continuously adopt and evaluate new technologies for business impact

Requirements

• 7+ years in backend development, with experience in a tech lead role
• Bachelor's/Master's/PhD in Computer Science or related field, or equivalent experience
• Proficient in C#, Kotlin, or Java
• Strong experience architecting and optimizing complex, data-driven systems
• Proven ability to lead technical strategy, mentor engineers, and drive delivery
• Excellent communication skills across distributed teams
• Fintech/payments domain experience is a plus
• Experience building scalable, cross-functional payment systems is a plus
• Experience using AI-assisted development tools (e.g., Copilot, Cursor, LLMs) is a plus

Benefits

EarnIn provides excellent employee benefits, including healthcare, internet/cell phone reimbursement, a learning and development stipend, and opportunities to collaborate with and travel to our Mountain View HQ and Bangkok Site.

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You will work with Solution Architects to guide customers in architecting production-grade ML & AI applications on Databricks, while aligning their technical roadmap with the continually evolving Databricks Data Intelligence Platform.

Your responsibilities will include:

• Architecting production-level ML & AI workloads for customers using our unified platform, including agents, end-to-end ML pipelines, training/inference optimization, integration with cloud-native services, MLOps, etc.

• Serving as a trusted practitioner for enterprise GenAI solutions, including RAG architectures, agentic systems (tool-calling agents, multi-agent orchestration, guardrails), natural language querying of structured data, AI evaluation and observability, and monitoring systems

• Building, scaling, and optimizing customer AI workloads and applying best-in-class MLOps to productionize these workloads across a variety of domains

• Providing advanced technical support to Solution Architects during the technical sale ranging from feature engineering, training, tracking, serving to model monitoring all within a single platform, as well as participating in the larger ML SME community in Databricks

• Collaborating cross-functionally with the product and engineering teams to represent the voice of the customer, define priorities and influence the product roadmap, helping with the adoption of Databricks' AI offerings

We are looking for someone with 5+ years of hands-on industry ML experience in at least one of the following areas:

• ML Engineer: Build and maintain production-grade cloud (AWS/Azure/GCP) infrastructure that supports the deployment of ML applications, including drift monitoring.

• AI Engineer: Experience with the latest techniques in LLMs & agentic systems including vector databases, fine-tuning LLMs, AI guardrail systems, and deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI

A graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience is also required.

Additionally, experience communicating and/or teaching technical concepts to non-technical and technical audiences alike is highly valued.

The salary range for this position is $180,000-$247,500 USD, depending on location.

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You will engage with new hires, current team members, and sales leaders to enhance their understanding of Stripe's products and sales strategies. You'll collaborate closely with cross-functional teams to ensure that training content is not only informative but also engaging and relevant.

Responsibilities:

• Lead onboarding and 101/201 live training sessions, ensuring an engaging and effective training experience for new hires
• Organize and facilitate sales skills workshops to uplevel seller performance in our SF hub
• Be prepared to travel to other areas of your region and support virtual delivery for the APAC team
• Build strong relationships with stakeholders to identify their unique enablement needs and sales skills gaps
• Collaborate with subject matter experts to develop engaging training materials, including presentations, role-plays, and interactive exercises that enhance efficiency and drive business outcomes
• Tailor content and information to various roles, segments, and sales motions, demonstrating empathy for sellers
• Assess training effectiveness through participant feedback and performance metrics, iterating on content and delivery methods as needed
• Provide ongoing coaching and support to sales team members to reinforce learning and drive continuous improvement
• Represent a macro-optimistic exothermic team and be the first face many see as an onboarding trainer
• Help drive a learning culture at Stripe by building strong relationships with stakeholders in your region

Requirements:

• 8+ years of experience in sales, sales enablement, or a related field, with a focus on onboarding or skills development
• A passion for teaching, a strong grasp of adult learning principles, and the ability to deliver engaging, hands-on programs while representing a positive and collaborative team
• Proven ability to design and deliver engaging training sessions, both virtual and in-person
• Experience coaching and delivering value selling or solution selling programs
• Excellent communication and presentation skills, with the ability to work cross-functionally with senior leaders and subject matter experts and to quickly convey complex concepts in simple terms
• Strong organizational skills and attention to detail, with the ability to manage multiple training initiatives simultaneously
• Experience in sales environments, ideally with an understanding of SaaS or financial technology solutions
• A proactive and adaptable mindset, capable of navigating ambiguity and changing priorities

Preferred Qualifications:

• Experience in a fast-paced, dynamic sales environment with a focus on quota attainment
• Familiarity with learning management systems (LMS) and e-learning tools
• Strong facilitation skills with experience in coaching and mentoring
• Certification in training methodologies or instructional design (e.g., ATD, CPLP, etc.) is a plus

At Stripe, we believe in nurturing talent and providing opportunities for professional growth. If you’re an enthusiastic and experienced training facilitator with a passion for empowering sales teams, we would love to hear from you!

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About the Position

As a Data Scientist on the platform prediction team, you will translate our probability of success predictions into measurable portfolio-level outcomes. You will architect core systems that let us rigorously evaluate signals from our AI-driven predictions in public and private equities and our internal portfolio.

This role sits at the intersection of quantitative finance, healthcare data, and AI-driven drug development. If you're excited about applying portfolio construction and risk management fundamentals to one of the most consequential prediction problems in healthcare, this is the role.

Responsibilities

• Work with the team to implement and maintain core portfolio engine: order management system, execution simulation layer, portfolio construction service, and performance tracking
• Design risk frameworks that quantify exposure across a portfolio of drug development bets with radically different risk profiles, timelines, and failure modes
• Run rigorous backtesting experiments with strict temporal constraints to evaluate Formation strategies against baseline approaches and measure marginal signal from new evidence sources
• Coordinate across the organization to integrate internal Formation data sources (clinical trial data, genomic evidence, real-world data) and proprietary tooling into portfolio analytics pipelines
• Work with product and engineering teams to build dashboards and reporting that communicate portfolio performance, risk metrics, and strategy comparisons to both technical and executive stakeholders
• Collaborate with the broader data science team to ensure portfolio-level evaluation feeds back into model improvement and evidence prioritization

About You

We are looking for a highly motivated and experienced Data Scientist to join our team. The ideal candidate will have a strong background in data science, machine learning, and software development, with a proven track record of delivering high-quality results in a fast-paced environment.

Requirements

• MS or PhD in a quantitative field (statistics, finance, physics, computational science, engineering, or related)
• 1-3 years in a quantitative research, data science, or analytics role , finance, healthcare, academic research, or consulting all count; substantive internships qualify
• Strong Python programming skills with experience in data-intensive workflows (pandas, numpy, scipy)
• Solid grasp of core portfolio construction and risk concepts: position sizing, rebalancing, Sharpe ratio, drawdown, volatility, benchmark comparison
• Demonstrated ability to work with messy, real-world datasets , comfortable with data wrangling, deduplication, and quality assessment
• Clear communicator who can present quantitative results to both technical peers and business stakeholders

Preferred Qualifications

• Experience with backtesting frameworks or portfolio simulation (vectorbt, Backtrader, or custom implementations)
• Exposure to healthcare, pharma, or biotech data (clinical trials, claims data, -omics, real-world evidence)
• Familiarity with alternative data in a research or investment context
• Experience with probability-of-success modeling, drug development decision analysis, or health economics
• Comfort with LLMs or AI/ML pipelines in a production or research setting
• Familiarity with dashboard/visualization tools (Streamlit, Plotly, Dash) and pipeline orchestration (Dagster, Airflow)

Total Compensation Range: $154,500 - $202,000

**Compensation Individual compensation is determined by several factors, including role scope, geographic location, and skills & experience. Your offer will reflect where you fall within the range based on these considerations. In addition to base salary, we offer equity, comprehensive benefits, and generous perks. If the posted range doesn't match your expectations, we still encourage you to apply!

**Where We Hire Formation Bio is prioritizing hiring in key hubs, primarily the New York City and Boston metro areas, with a hybrid model requiring 3 days per week in office. Applicants from the Research Triangle (NC) and San Francisco Bay Area may also be considered. Please apply only if you reside in these locations or are willing to relocate.

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About the Role

At Pave, we're building the industry's leading compensation platform. As an AI Engineer on the Paige team, you'll shape the technical vision and execution of our autonomous AI compensation analyst. You'll work with a team of engineers and data scientists to build the product end-to-end and take it to market.

Key Responsibilities

• Develop and maintain production systems using LLMs, agentic architectures, and retrieval systems
• Collaborate with cross-functional teams to design and implement features end-to-end
• Apply pragmatic engineering judgment to balance speed and quality
• Communicate clearly and effectively with both technical and non-technical stakeholders

What We Offer

• Competitive salary and equity package
• Best-in-class medical, dental, and vision coverage
• Unlimited PTO and flexible work arrangements
• Quarterly education stipend and opportunities for professional growth

Culture

At Pave, we value intellectual honesty, a willingness to play to win, and a commitment to upholding the highest standards. We're a hybrid culture that brings teams together in person on Monday, Tuesday, Thursday, and Friday, with a weekly Team Sync on Fridays.

How to Apply

If you're ready to help shape the future of compensation alongside a talented team, we'd love to meet you. Please submit your application, including your resume and a cover letter, to [insert contact information].

Note

This job description is subject to change based on business needs and requirements. Pave is an equal opportunity employer and welcomes applications from diverse candidates.

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We are seeking a Senior Software Engineer to join our Quality Platform team at Airbnb. The Quality Platform team is responsible for building the infrastructure that prevents bugs and ensures a seamless experience for millions of hosts and guests.

As a Senior Software Engineer, you will play a key role in evolving our Quality Platform. You will bridge the gap between product engineering and infrastructure, ensuring that our Android codebase remains highly testable and resilient as it scales.

Responsibilities:

• Build AI-Native Tooling: Move beyond traditional automation by implementing AI-driven agents that optimize our CI/CD pipelines and provide intelligent feedback to developers.

• Enhance Developer Velocity: Identify and resolve systemic bottlenecks in the development lifecycle, allowing teams to move faster without compromising quality.

• Advocate for Quality by Design: Work directly with product teams to guide architectural decisions, ensuring that new features are modular and testable from the first line of code.

• Ship High-Scale Infrastructure: Own the development and maintenance of frameworks used by hundreds of engineers across Airbnb, ensuring they are performant, reliable, and easy to use.

A Typical Day:

• Hands-on Development: Write high-quality, performant Kotlin code to extend testing frameworks and build AI-powered developer tools, leveraging LLMs to accelerate development workflows.

• Technical Ownership: Take ownership of key components of our Automated Quality Platform, ensuring operational excellence and high availability (24x7) of our testing infrastructure.

• Design & Review: Participate in deep-dive design reviews for new Android features, providing expert guidance on modularity and testability patterns.

• Applied AI: Implement LLM-based solutions for smart test orchestration, test case generation, and autonomous test discovery to reduce CI feedback loops.

• Cross-Functional Collaboration: Partner with Product and Mobile Infrastructure teams to align platform capabilities with the needs of the broader engineering org.

• Mentorship: Review code and provide technical guidance to peers, fostering a culture of commitment to craft and engineering rigor.

Your Expertise:

• Experience: 5+ years of professional Android development experience (or 2+ years with a PhD) in a fast-paced, high-growth tech environment.

• Technical Mastery: Strong proficiency in Kotlin and the Android SDK. You have a solid understanding of modern Android architecture and the Gradle build lifecycle.

• Infrastructure Experience: Demonstrated expertise in building or maintaining test automation frameworks (e.g., Espresso, Compose Test) at scale.

• CI/CD & Tools: Familiarity with CI/CD orchestration and a passion for building tools that improve the developer experience.

• AI Curiosity: A strong interest or hands-on experience in leveraging AI/LLMs to solve engineering productivity or quality challenges.

• Problem Solving: Proven ability to navigate complex, ambiguous codebases and implement best-in-class solutions.

• Communication: Excellent communication skills with the ability to facilitate technical discussions across cross-functional teams.

Our Commitment To Inclusion & Belonging:

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions.

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This role sits at the intersection of product thinking and full-stack engineering. You will work directly with researchers and engineers to deeply understand their workflows, identify bottlenecks, and rapidly ship solutions that multiply their productivity. Whether you're building human feedback interfaces for model evaluation, creating platforms for experiment orchestration, or developing novel visualization tools for understanding model behavior, your work will directly accelerate our mission to build safe, reliable AI systems.

We're looking for someone who can operate with high agency in an ambiguous environment,someone who can be dropped into a research team, quickly develop domain expertise, and independently drive impactful projects from conception to delivery.

No ML or Research experience is required.

Responsibilities:

• Build and maintain full-stack applications and infrastructure that researchers use daily to conduct experiments, collect feedback, and analyze results
• Partner closely with research teams to understand their workflows, pain points, and requirements, translating these into technical solutions
• Design intuitive interfaces and abstractions that make complex research tasks accessible and efficient
• Create reusable platforms and tools that accelerate the development of new research applications
• Rapidly prototype and iterate on solutions, gathering feedback from users and refining based on real-world usage
• Take ownership of complete product areas, from understanding user needs through design, implementation, and ongoing iteration
• Contribute to technical strategy and architectural decisions for research tooling
• Mentor other engineers and help establish best practices for research application development

You may be a good fit if you:

• Have 5+ years of software engineering experience with a strong focus on full-stack development
• Excel at rapid iteration and shipping,you can move from concept to working prototype quickly
• Have experience building tools, platforms, or infrastructure for technical users (engineers, researchers, data scientists, analysts, etc.)
• Demonstrate high agency and ability to operate independently in ambiguous environments
• Can quickly develop deep understanding of complex technical domains
• Have strong product instincts and can identify the right problems to solve
• Are proficient with modern web technologies (React, TypeScript, Python, etc.)
• Have a track record of building user-facing applications that are actually used and loved by their target audience
• Communicate effectively with both technical and non-technical stakeholders
• Care about the societal impacts of your work and are motivated by Anthropic's mission

Strong candidates may also have:

• Experience building research tools, scientific software, or experimentation platforms
• Background in machine learning, AI research, or working closely with ML researchers
• Founded or been an early engineer at a startup, particularly one focused on developer or researcher tools
• Built open-source tools or platforms with active user communities
• Experience with data visualization, interactive interfaces, or novel interaction paradigms
• Contributed to engineering platforms or internal tooling at scale (similar to Heroku, Vercel, or other platform-as-a-service products)
• Experience leveraging AI/LLMs to build more powerful or efficient tools
• Previous work in creative tools, artist tools, or other domains requiring deep user empathy
• Domain knowledge in areas like human-computer interaction, systems safety, or AI alignment

Representative projects:

• Building interfaces for collecting and managing human feedback on model outputs at scale
• Creating experiment orchestration platforms that make it easy to launch, monitor, and analyze complex research runs
• Developing visualization tools that help researchers understand model behavior and identify failure modes
• Designing reusable components and frameworks that enable rapid development of new research applications
• Building sandboxed execution environments for safely running AI-generated code

Annual compensation range for this role is $300,000-$405,000 USD.

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While traditional NLP focuses on analyzing static text, your work will center on real-time, multimodal systems that can listen, reason, and take action during live customer interactions.

A major focus of the team is advancing DialpadGPT, our proprietary LLM, specifically optimizing it to drive orchestrated agentic workflows and handle complex task execution.

Beyond the technical skills, we are a team that values collaboration, continuous learning, and the application of diverse perspectives to solve complex problems.

Collaboration will be key as you work alongside our engineering, design, and product teams to build groundbreaking agentic applications.

If you're passionate about agentic and multimodal AI and contributing to a team that's changing the face of business communications, you'll find yourself right at home with us.

This position reports to the Senior Manager of the NLP team and has the opportunity to be based in Vancouver, BC.

Key responsibilities include:

• Research and develop state-of-the-art algorithms for autonomous voice agents, specifically focusing on real-time speech processing and reasoning loops.

• Advance DialpadGPT: Design and execute distributed training strategies to optimize our proprietary LLMs for agentic behaviors, including precise tool use, instruction following, and latency-constrained generation.

• Conduct rigorous evaluation and monitoring of model performances and troubleshoot issues with a keen understanding of resultant business impacts.

• Design and implement orchestration layers that effectively chain LLMs with external tools and APIs to solve complex customer problems autonomously.

• Work with large-scale multimodal datasets (text, audio) to improve model robustness and alignment.

• Collaborate with engineering, product, and design teams to deploy scalable, low-latency models and algorithms in production.

• Submit papers to top-tier academic conferences (ACL, EMNLP, NeurIPS) and contribute to the team’s research culture.

To succeed in this role, you'll need:

• A Master’s or PhD degree in Computer Science, Machine Learning, Computational Linguistics, or a related quantitative field.

• 2+ years of industry experience in Machine Learning/NLP for Master’s degree holders, or 1+ years for PhD holders.

• Deep understanding of LLMs: Demonstrated experience with training, fine-tuning (PEFT/LoRA), and alignment techniques (RLHF/DPO) for specific domains or tasks.

• Experience with Agentic Systems: Familiarity with building autonomous agents, including concepts like tool use, function calling, reasoning chains (CoT), and memory management.

• Strong proficiency in Python and PyTorch, with the ability to write clean, production-ready research code.

• Research Track Record: A history of publishing in top-tier conferences (ACL, EMNLP, NeurIPS, ICASSP) is highly valued.

• Multimodal Awareness: Familiarity with speech technologies (ASR, TTS) or processing real-time audio streams is a strong plus.

• Ability to bridge the gap between research and product, translating complex technical concepts into business value.

• Familiarity with version control tools like Git for collaborative projects.

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Carta connects founders, investors, and limited partners through world-class software, purpose-built for everyone in venture capital, private equity and private credit.

Trusted by 65,000+ companies in 160+ countries, Carta’s platform of software and services lays the groundwork so you can build, invest, and scale with confidence.

The Problems You'll Solve

As Carta’s Head of GTM Content, you will lead a talented, experienced team of editors, content strategists, and writers producing best-in-class B2B content.

You’ll ensure the editorial team delivers timely, accurate, and high-impact content related to the evolving private markets ecosystem, including private equity firms, venture capital firms, private credit firms, and limited partners who support private companies.

Responsibilities

Team and editorial leadership:

• Lead and manage a team of senior editors and writers to cultivate a high-functioning, collaborative, and purpose-driven editorial team that is tightly aligned with the wider marketing org and indispensable to Carta’s overall mission

• Champion the role of content and represent the team in companywide, big-picture strategic conversations.

• Infuse creativity while pushing the boundaries on operational excellence

Content strategy and planning:

• Provide an editorial vision that drives content strategies supporting business-wide goals for audience engagement, acquisition, retention, and conversion

• Partner closely with leaders of the SEO, product marketing, creative, and demand-generation teams to drive omnichannel content campaigns

• Develop repeatable and scalable editorial processes for ideation, creation, optimization, distribution, and governance

Performance and analytics:

• Partner with internal marketing leaders to obtain greater visibility of editorial content performance through the funnel

• Lead a results-based editorial culture that prioritizes data-rich insights to track content performance, inform editorial decisions, and optimize strategies

• Lead the development of reporting frameworks that measure engagement and ROI, and communicate results with clarity to leaders including the C-suite

The Team You'll Work With

At Carta, the Communications and Content team plays a vital role in shaping the company’s brand, messaging, and public image.

Their responsibilities typically span several key areas including PR, Corporate Communications, Content Marketing, Social Media, Influencer Relations, and Internal Comms.

Together this team is Carta’s storytelling engine – responsible for communicating the company’s story and impact, both internally and externally, in a clear, compelling, and consistent way that supports business goals and builds trust with stakeholders.

About You

• Track record of managing teams and processes that produce best-in-class B2B content,and a record of demonstrating out-of-the-box, creative thinking that can future-proof content in a rapidly changing environment

• Deep understanding of the private markets, including startup fundraising, venture capital, private equity, private credit loan operations, and limited partner investing

• Advanced, industry-leading knowledge of SEO, LLMs, AI tools, and data-driven content strategies, and a track record of deeply leveraging emerging tools to develop editorial processes

• Demonstrated knowledge of global ecosystems, including track record of producing private markets content related to non-U.S. regions including Africa, Asia/Pacific Islands, the Middle East, and the U.K.

• Demonstrated success in building scalable content programs that deeply engage target audiences and move them through the funnel

• Outstanding writing, editing, and research skills; comfortable producing and refining technical and analytical content

• Strong cross-functional communication skills and the ability to collaborate across departments in a fast-paced, high-growth setting

Salary

Carta’s compensation package includes a market competitive salary, equity for all full time roles, exceptional benefits, and, for applicable roles, commissions plans.

Our minimum cash compensation (salary + commission if applicable) range for this role is: $176,000 - $220,000.

Final offers may vary from the amount listed based on geography, candidate experience and expertise, and other factors.

Disclosures

• We are an equal opportunity employer and are committed to providing a positive interview experience for every candidate.

• If accommodations due to a disability or medical condition are needed, please connect with the talent partner via email.

• Carta uses E-Verify in the United States for employment authorization.

• For information on our data privacy policies, see Privacy, CA Candidate Privacy, and Brazil Transparency Report.

• Please note that all official communications from us will come from an @carta.com or @carta-external.com domain.

Report any contact from unapproved domains to security@carta.com.

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Working closely with our Sales, Product, and Engineering teams, you'll guide a focused portfolio of customers from technical discovery through successful deployment. You'll combine deep engineering expertise with customer-facing skills to help customers unlock the full potential of Claude APIs and move their products closer to the frontier, while maintaining our high standards for safety and reliability.

Responsibilities

• Serve as a specialist technical advisor to Anthropic customers as they deploy new products & workflows with our models: from discovery through deployment, coordinating internally across multiple teams to drive customer success

• Partner with account executives and solutions architects to translate customer business requirements into technical solutions

• Influence technical architecture decisions and customer product strategy by developing customized pilots, prototypes, and evaluation suites

• Lead hands-on technical workshops and code reviews with customer engineering teams

• Identify common design patterns and contribute insights back to our Product and Engineering teams

• Create scalable public and internal assets, documenting the latest LLM prompting, evaling, agentic, and architecture techniques

• Maintain strong knowledge of the latest developments in LLM capabilities, implementation patterns, and AI product development stacks

• Travel occasionally to customer sites for workshops, implementation support, and building relationships

• Attend conferences, lead speaking engagements, write blog posts and white papers on topics surrounding the AI space

Requirements

• 4+ years of experience in technical roles such as Forward Deployed Engineer, Software Engineer or Technical Product Manager with a desire to work closely with customers. Former technical founders are also encouraged to apply.

• Production experience with LLMs including advanced prompt engineering, agent development and frameworks, evaluation frameworks, transcript analysis, MCP, and deployment at scale

• Strong programming skills with proficiency in Python or TypeScript and experience building production applications

• Ability to navigate ambiguity and execute across domains with intellectual openness, finding simple solutions to complex problems

• High cooperation mindset for cross-organizational collaboration, balancing competing priorities with integrity

• Passion for advancing safe, beneficial AI systems through creative technical applications

• Exceptional communication skills to convey technical concepts to diverse stakeholders while maintaining a low ego and collaborative approach

Benefits

• Competitive compensation and benefits

• Optional equity donation matching

• Generous vacation and parental leave

• Flexible working hours

• Lovely office space in which to collaborate with colleagues

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Location: United States

Department: Operations

Job Description:

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way.

The Community You Will Join:

Airbnb is a global hospitality platform that connects travelers with unique accommodations and experiences around the world. Our mission is to create a world where anyone can belong anywhere.

Community Blueprint is a team under Global Operations that aims to improve the quality of the end-to-end customer journey and bridge team silos across product, operations, and policy. To do this, we need to be experts in the guest and Host experience and in how the product, operations, policies function together to deliver the Airbnb experience.

As part of the Community Blueprint team, your role will be instrumental in driving data-driven decision-making, connecting data across product & operations, and enhancing the guest and Host experience.

The Difference You Will Make:

We are seeking a highly experienced and skilled leader with deep expertise in customer journey analysis, strategic planning, and team development. As the Senior Manager, you are a leader that will be responsible for driving forward customer experience excellence, developing insights that identify user experience gaps, and growing the team’s impact on the business.

The ability to connect the dots across the end-to-end customer journey and across different teams will be critical to success. This role will also be presenting to and influencing leaders at the highest level, meaning strong communication skills will be essential.

This role will be part of the Frontline Insights & Execution (FIX) team within Community Blueprint. This is a highly cross-functional team, this means you will collaborate with many different functions across all of Airbnb to drive strategic initiatives and inform decisions that will ultimately improve the guest and host experience.

We are looking for a scrappy self-starter with an entrepreneurial mindset who thrives in ambiguity and can deeply understand the nuances of our rapidly evolving business and use data to make key decisions.

A Typical Day:

• Lead, mentor, and develop a high-performing team, providing regular feedback, coaching, and performance evaluations.

• Foster a collaborative and supportive team environment that encourages growth, knowledge sharing, and innovation.

• Oversee workload management, resource allocation, and project prioritization for the team.

• Develop and implement key performance indicators (KPIs) to measure team effectiveness and impact.

• Collaborate with cross-functional leaders to align with broader company goals and objectives.

• Analyze quantitative and qualitative data across the end-to-end customer journey to drive business decisions.

• Identifying customer issues and understanding the what as well as investigating the why.

• Leverage LLMs/generative AI tools to enhance the effectiveness of the team.

• Develop strong working relationships and collaborative partnerships with the various internal teams such as Product, Operations, Engineering, Training, Knowledge Management, Incident Management, Business Process Improvement, Partner Management, Finance, Research, and others.

• This is a global program, which means this role will be working with people from many different time zones and requires flexibility in the hours they’re available to take meetings.

• Stay up-to-date with the latest industry trends and advancements in quantitative and qualitative data analysis techniques.

Your Expertise:

• An undergraduate degree with a strong preference for candidates holding an MBA or equivalent advanced degree, with 12+ years of industry experience in a General Manager, Strategy Manager, Product Insights, Product Operations or equivalent role.

• Proficiency in SQL, data analysis, and data visualization.

• Proficiency in Jira and Airtable (optional).

• Strong technical data skills, ability to connect data across multiple areas.

• Self-starter, thrives in ambiguity, and has an investigator mindset of wanting to get to the bottom of problems.

• Strong problem-solving and critical thinking abilities, with a keen attention to detail.

• Excellent communication and presentation skills, with the ability to effectively communicate complex concepts to both technical and non-technical stakeholders.

• Exceptional stakeholder management skills, with a proven ability to collaborate and influence across functions.

• An agile, growth-minded approach, demonstrated through a history of driving projects from ideation to impact.

• Robust business acumen, strategic thinking skills, and the ability to make informed judgments.

• Experience managing a team including performance management and goal setting.

• Experience managing projects involving cross-functional teams.

• Understanding of LLMs and desire to continue to learn in the AI space.

• Flexible and can deal effectively with changes in priorities or ambiguity.

• Prior experience in the technology industry or a fast-paced, data-driven environment is preferred

Joining the Airbnb team as a Senior Manager of the Community Blueprint Team will provide you with an exciting opportunity to contribute to the growth and success of a global technology company. If you are a highly analytical, detail-oriented, and strategic thinker with a passion for data-driven decision-making, we would love to hear from you.

Your Location:

This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed to with your manager. While the position is Remote Eligible, you must live in a state where Airbnb, Inc. has a registered entity. Click here for the up-to-date list of excluded states. This list is continuously evolving, so please check back with us if the state you live in is on the exclusion list If your position is employed by another Airbnb entity, your recruiter will inform you what states you are eligible to work from.

Our Commitment To Inclusion & Belonging:

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply. We strive to also provide a disability inclusive application and interview process. If you are a candidate with a disability and require reasonable accommodation in order to submit an application, please contact us at: reasonableaccommodations@airbnb.com. Please include your full name, the role you’re applying for and the accommodation necessary to assist you with the recruiting process. We ask that you only reach out to us if you are a candidate whose disability prevents you from being able to complete our online application.

How We'll Take Care of You:

Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.

Pay Range $188,000-$235,000 USD

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Key responsibilities include:

• Driving high-impact scientific work across GenAI-powered labeling and evaluation systems
• Identifying opportunities where LLMs and related methods can improve quality, speed, coverage, and cost efficiency
• Developing prototypes that demonstrate value in areas such as prompt optimization, task decomposition, quality estimation, routing, and human-in-the-loop workflows
• Designing rigorous measurement frameworks to evaluate model performance, workflow outcomes, and operational tradeoffs
• Partnering with engineering, product, and data science teams to shape roadmaps and productionize successful approaches
• Establishing strong standards for trustworthiness, including bias measurement, calibration, quality control, and responsible oversight
• Creating reusable methods and frameworks that can scale across teams and use cases

Requirements include:

• 10+ years of combined post-graduate academic and industry experience applying scientific methods to solve real-world problems on large-scale data
• Deep hands-on experience as an individual contributor solving technically complex, high-impact data science or ML problems
• Strong experience applying LLMs or other generative AI techniques to practical workflows, systems, or products
• Demonstrated ability to turn ambiguous problems into rigorous analyses, experiments, prototypes, and scalable solutions
• Proven track record of writing high-quality code and using technical work to influence product or platform direction
• Strong cross-functional collaboration skills and a track record of influencing leaders and peers through data and technical judgment
• Strong business and product sense with the ability to define meaningful success metrics and prioritize high-value opportunities
• Self-directed learning mindset and comfort working in a rapidly evolving technical landscape
• Experience with labeling systems, evaluation frameworks, human judgment workflows, or internal AI tooling is strongly preferred

In-office requirement statement: This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country.

Relocation statement: This position is not eligible for relocation assistance.

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The ideal candidate will have a bachelor's degree in Computer Science, Software Engineering, or a related field, 4+ years of experience in a software or infrastructure engineering industry, strong experience operating services in production and at scale, deep experience with Go as the primary programming language, experience with infrastructure-as-code, CI/CD systems, and containerization, understanding of system design, scalability, and efficiency, extensive experience with Artifactory, Cloudsmith, and passion for improving developer experience and enabling other engineers to do their best work.

In addition to the above requirements, preferred qualifications include experience integrating or enabling tools that leverage LLMs or code intelligence for developers, experience with KubeVirt, KataContainers, and a willingness to learn and adapt to new technologies and processes.

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Responsibilities:

• Develop the long-term vision, strategy, and day-to-day operations for Professional Services enablement at Stripe.
• Establish KPIs and analytics to track the impact of enablement initiatives and make data-driven decisions.
• Create and publish Professional Services enablement calendar.
• Communicate enablement strategies, program progress, and readiness metrics clearly and concisely to senior ProServ leadership.
• Collaborate with a globally distributed team across multiple time zones and serve as the crucial bridge between Product, GTM Enablement, Partners, and Professional Services leadership, ensuring all teams are aligned on enablement priorities and product readiness.
• Understand the role of consulting at Stripe so that you confidently build new training programs and content focused on soft skill enablement.
• Translate complex product capabilities into specialized learning paths and actionable enablement resources across Stripe’s technical landscape.
• Stay on the pulse of industry trends and competitive landscapes, adapting enablement priorities to maintain Stripe's technical edge.
• Build aesthetically superb courseware and documentation alongside scalable enablement assets (e.g., technical deep-dives, playbooks, certification programs, and hands-on technical labs).
• Orchestrate and collaborate with Subject Matter Experts (SMEs), including Product and Product Marketing, to curate high-impact technical content.
• Design and deliver comprehensive onboarding programs, ongoing training, and just-in-time learning resources to keep the Professional Services teams at the cutting edge.
• Cultivate a program of continuous peer-to-peer learning that empowers top-performing consultants to share best practices and field-tested technical solutions.
• Identify skill and knowledge gaps, then partner cross-functionally to build innovative enablement programs that drive measurable improvements in satisfaction, productivity, and revenue generation.
• Be a key advocate and support for change management and best practices throughout the organization.

Requirements:

• 10+ years of experience in a technical consulting or enablement role.
• Knowledge of adult learning principles and the ability to incorporate them into the curriculum.
• Proven track record of designing and delivering highly effective enablement programs that drive measurable improvements in sales and delivery performance.
• Strong project management skills with the ability to multitask, prioritize, and execute in a fast-paced environment.
• Excellent communication and presentation skills, with experience engaging both technical and non-technical stakeholders.
• Demonstrated ability to work cross-functionally and build productive relationships with teams across the organization.
• Passion for continuous learning and a solutions-oriented mindset.
• Experience with content creation, curation, and knowledge management platforms.

Preferred qualifications:

• Experience developing content for technical certifications.
• Professional experience using e-learning software and/or LMS.
• Experience working with payment industry and/or consulting.

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We work closely with some of the most advanced AI teams in the world, helping them build, optimize, and scale their ML and GenAI workflows across industries such as computer vision, robotics, natural language processing, and large language models (LLMs).

We’re hiring an AI Solutions Engineer, Post-Sales to help customers solve real-world problems by enabling them to implement and scale ML pipelines and agentic workflows using Weights & Biases. In this role, you’ll collaborate with engineering teams to ensure smooth onboarding and adoption, act as a trusted advisor on best practices, and represent the voice of the customer internally.

You will partner directly with leading AI teams to optimize workflows, share technical expertise, and influence our product roadmap based on real-world customer feedback.

This is an ideal opportunity for ML practitioners who are customer-focused and eager to work with top AI companies globally.

Responsibilities

• Collaborate with engineering teams to ensure smooth onboarding and adoption of Weights & Biases
• Act as a trusted advisor on best practices for implementing and scaling ML pipelines and agentic workflows
• Represent the voice of the customer internally and influence our product roadmap based on real-world customer feedback
• Partner directly with leading AI teams to optimize workflows and share technical expertise

Requirements

• 3–5 years of relevant experience in a similar role
• Strong programming proficiency in Python
• Hands-on experience enabling production-grade ML systems, with a focus on training and inference pipelines, experiment tracking, deployment patterns, and observability using deep learning frameworks (TensorFlow/Keras, PyTorch/PyTorch Lightning) and MLOps tooling (e.g. Airflow, Kubeflow, Ray, TensorRT)
• Familiarity with cloud platforms (AWS, GCP, Azure)
• Experience with GenAI/LLMs and related tools (e.g. LangChain/LangGraph, HuggingFace Transformers, Pinecone, Weaviate)
• Strong experience with Linux/Unix
• Excellent communication and presentation skills, both written and verbal
• Ability to break down and solve complex problems through customer consultation and execution

Preferred

• Background in robotics
• TypeScript experience
• Proficiency with Fastai, scikit-learn, XGBoost, or LightGBM
• Background in data engineering, MLOps, or LLMOps, with tools such as Docker and Kubernetes
• Familiarity with data pipeline tools

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You will collaborate closely with product, platform, and data teams to build AI capabilities that transform how healthcare data is explored, understood, and operationalized. Your work will involve designing, building, and deploying agent-based AI pipelines integrated into real customer-facing products, as well as building internal AI productivity tools that accelerate engineering workflows across Komodo.

In this role, you will have the opportunity to work on a wide range of projects, from developing AI-powered applications to integrating AI capabilities across backend services and product interfaces. You will also contribute reusable patterns to Komodo's AI infrastructure and internal tooling ecosystem.

To be successful in this role, you will need to have experience building production-grade AI systems or AI-powered applications, strong proficiency in Python, and experience working with LLMs, prompt engineering, or agent-based architectures. You will also need to be able to integrate AI capabilities across backend services and product interfaces, and have experience designing evaluation frameworks, testing strategies, or monitoring systems for AI features.

If you are passionate about using AI to drive innovation and improvement in healthcare, and have the skills and experience to succeed in this role, we encourage you to apply.

Key Responsibilities

• Design and deploy end-to-end AI solutions that power real products and internal tools
• Collaborate closely with product, platform, and data teams to build AI capabilities that transform how healthcare data is explored, understood, and operationalized
• Develop agent-based AI pipelines integrated into real customer-facing products
• Build internal AI productivity tools that accelerate engineering workflows across Komodo
• Contribute reusable patterns to Komodo's AI infrastructure and internal tooling ecosystem

Requirements

• Experience building production-grade AI systems or AI-powered applications
• Strong proficiency in Python
• Experience working with LLMs, prompt engineering, or agent-based architectures
• Ability to integrate AI capabilities across backend services and product interfaces
• Experience designing evaluation frameworks, testing strategies, or monitoring systems for AI features

Nice to Have

• Healthcare data expertise
• Experience with distributed computing frameworks (e.g., Spark, Snowflake, Databricks) for large-scale data processing

Location

This role is located in San Francisco, California, and is available for remote work.

Benefits

• Comprehensive health, dental, and vision insurance
• Flexible time off and holidays
• 401(k) with company match
• Disability insurance and life insurance
• Leaves of absence in accordance with applicable state and local laws and regulations and company policy

Equal Opportunity Employer

Komodo Health is an equal opportunity employer and welcomes applications from all qualified candidates. We are committed to diversity and inclusion in the workplace and strive to create a work environment that is free from discrimination and harassment.

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We believe skill with AI is fundamental to human agency. Education Labs sits inside Product Research, which means we build learning products with a front-row seat to what's coming. We're close to the people shaping Claude's next capabilities, and our job is to make sure the world can actually use them.

Responsibilities

Build at the frontier - Co-develop vision and own strategy and execution for AI-native learning products , the adaptive systems, assessments, and in-product experiences that will define how people learn with and about frontier AI Work closely with research teams to understand emerging capabilities and what they unlock for learners , you're translating research into product, not waiting for a spec Prototype and experiment to validate ideas quickly, using Claude and our internal tools as building blocks Anticipate how capability shifts change the product and build with that trajectory in mind Stay close to learners , run user research, watch real people move from "I don't understand this" to "I could teach this," and let what you observe reshape what we build

Be a thought partner Push the team's thinking on what education should look like as AI capabilities accelerate , help us spot what we're missing, not just execute what we've already decided Bring product rigor to a team that's scaling fast: clear priorities, sharp tradeoffs, honest metrics that connect learning to real behavior change Act as a bridge between research, product, GTM, marketing, comms, and the education team, translating in all directions

See the whole picture Collaboratively define success metrics grounded in demonstrated understanding, skill progression, and lasting agency , not time-on-site or completion counts Keep a hand in the success of adjacent team efforts, helping the overall education portfolio work as a system rather than a collection of projects Partner across Anthropic , product teams, research, GTM, societal impacts, marketing , to keep education woven into how we ship and scale Run the program, not just the product: drive stakeholder alignment across technical and non-technical partners, keep workstreams on track, and own the operational rhythm that turns strategy into shipped work

You may be a good fit if you have

5+ years in product management, with a track record of shipping products from zero to one and seeing them through to real impact Technical fluency , you're comfortable with AI tools, can prototype with Claude, and hold your own in conversations with researchers and engineers Genuine curiosity about frontier AI , you follow what's emerging, you play with new capabilities, and you have opinions about where things are heading Comfort with ambiguity and wide scope , you make good calls with incomplete information and you're not precious about where your job ends A track record as a force multiplier on small teams , you make the people around you more effective, not just your own roadmap Strong written and verbal communication , you can write a crisp spec, present to leadership, and synthesize messy stakeholder input into a clear direction Conviction that education should build agency, not dependency , you want to teach people to think with AI, and you believe that matters

Strong candidates may also have

Experience working closely with research or applied science teams, or a background that makes you fluent in how research becomes product Background in learning products, developer education, or curriculum design Founder experience or time at an early-stage company where scope was wide and you wore many hats Familiarity with how people actually learn , learning science, instructional design, or strong instincts from having taught something yourself Experience building with LLMs as core product infrastructure, not just as a feature

What this role is not

This is a hands-on IC product, project, and program management role. You'll shape strategy, push the team's thinking, and have real influence over what education at Anthropic becomes, and coordinate complex execution across multiple stakeholders and teams , but it doesn't involve people management. If you're looking to immediately lead a team, this isn't the right fit. If you want broad scope and high autonomy as a builder, it might be.

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The ideal candidate will have a minimum of 7 years of experience in a software or infrastructure engineering industry, deep experience operating services in production and at scale, proficiency in Go as your primary programming language, strong experience with infrastructure-as-code, CI/CD systems (e.g., GitHub Actions, ArgoCD), and containerization (e.g., Docker, Kubernetes), expertise in leading scale system design, scalability, and efficiency, experience with third-party vendors like Artifactory, and passion for improving developer experience and enabling other engineers to do their best work.

In addition to the required skills, preferred skills include experience integrating or enabling tools that leverage LLMs or code intelligence for developers (e.g., GitHub Copilot, Cody, custom LLM integrations), experience with KubeVirt, KataContainers, and experience with LangGraph/LangChain.

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The impact you'll have:

• Create novel, never-seen-before interfaces for GenAI agents that manage complex workflows while keeping the human in the loop through inspectability and transparency
• Partner closely with product management, design, and other engineering teams to build intuitive, scalable, and extensible solutions that drive user & business growth
• Lead by example with hands-on full-stack software development to create dynamic, user-centric experiences
• Enable mechanisms that can drive product-led growth, through seamless onboarding and sharing capabilities
• Direct the future of intuitive agentic applications at Databricks, in collaboration with cross-functional teams of innovative software engineers, product managers, and designers
• Drive the strategy for building end-to-end AI feature development by designing, building, and maintaining systems that are scalable, reliable, and performant.

What we look for:

• 5+ years of experience with HTML, CSS, and JavaScript
• Demonstrated product mindset with the ability to translate ambiguous customer problems into scrappy MVPs and iterate quickly based on data and user feedback.
• You care that AI features feel intuitive, trustworthy, and helpful, not just bolted on to an existing app
• High ownership and bias for action in 0→1 environments: you are comfortable making pragmatic trade-offs, operating with incomplete information, and driving projects from idea through launch and adoption.
• Strong ability to collaborate across product, engineering, and design teams to align technical strategy with company growth objectives.
• Experience with modern JavaScript frameworks (e.g., React, Angular, or VueJs/Ember)
• 5+ years of experience with server-side web technologies (eg: Node.js, Java, Python, Scala, C#, C++,Go)
• Proven experience building and shipping end-to-end generative AI products
• Deep familiarity with LLMs and generative AI, including hands-on experience with techniques like retrieval-augmented generation (RAG), prompt design, evaluation, and monitoring AI quality and safety in production.

Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.

Local Pay Range $166,000-$225,000 USD

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To be successful, you will have experience marketing to developers and need to become comfortable with the technical aspects of Elastic's products and solutions, including LLM and SLMs, the markets they play in, as well as, the creative aspects of positioning technology through messaging and narratives that are compelling, authentic, and differentiated!

Key responsibilities include: Acting as a technical product marketing lead for the Jina AI, and taking ownership of the strategy to drive awareness and market penetration of key capabilities Serving as an internal authority on the developer persona Crafting compelling, technical and differentiated outbound product messaging and content (like blogs, videos, tutorials, web pages, webinars that resonate with developers) Enabling the field on our solutions, through training and content (e.g. pitch decks and playbooks.) Building and implementing plans to reach and champion relationships with our developer and technology partner ecosystem Planning and implementing product launches (with operational marketing teams), including creating launch materials and content to support and coordinate with team members Building a positive partnership with peers in Product Management, Engineering and Community to effectively launch new features and products and engage with users Attending and presenting at Elastic events, third party trade shows and other events to help showcase our products to technical audiences.

What you bring: 7-10 years of experience in product marketing in a technical environment Proven track record of effectively marketing technical products to developers or technical audiences Curiosity about the 'how' of technology to tell compelling stories about the 'why' Ability to work in a very cross functional role, with a highly distributed team Experience driving a GTM and crafting high quality assets Be a spokesperson for product capabilities and Elastic at large for internal and external audiences - including webinars, trainings, and analyst briefings Excellent spoken and written communication skills

Bonus considerations: Direct experience with developers, and audiences that build applications Product marketing experience with technical AI, SaaS or infrastructure products preferred Experience crafting engaging content for developers, including blog posts, decks, videos, etc. Comfortable marketing to technical leaders Familiarity with Elasticsearch, Elastic Platform or our solutions

Compensation for this role is in the form of base salary. This role does not have a variable compensation component. The typical starting salary range for new hires in this role is $135,700-$214,700 USD. In select locations (including Seattle WA, Los Angeles CA, the San Francisco Bay Area CA, and the New York City Metro Area), an alternate range may apply as specified below.

Additional information: As a distributed company, diversity drives our identity. Whether you're looking to launch a new career or grow an existing one, Elastic is the type of company where you can balance great work with great life. Your age is only a number. It doesn't matter if you're just out of college or your children are; we need you for what you can do.

We strive to have parity of benefits across regions and while regulations differ from place to place, we believe taking care of our people is the right thing to do.

Competitive pay based on the work you do here and not your previous salary Health coverage for you and your family in many locations Ability to craft your calendar with flexible locations and schedules for many roles Generous number of vacation days each year Increase your impact - We match up to $2000 (or local currency equivalent) for financial donations and service Up to 40 hours each year to use toward volunteer projects you love Embracing parenthood with minimum of 16 weeks of parental leave

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This role sits at the intersection of startup ecosystem development and hands-on technical activation. Your primary mandate is driving adoption across the startup funnel , turning ecosystem touchpoints into active, building developers on Anthropic's platform. You'll work closely with the Startups GTM team to convert ecosystem relationships , with VCs, accelerators, and founder communities , into active, building developers.

Responsibilities:

• Drive Net New Logo Acquisition Through Developer Enablement
• Lead hands-on developer onboarding experiences at ecosystem events that convert startup founders and their engineers from first API interaction to committed platform adoption
• Build scalable enablement programs , hands-on workshops, build-a-thons, and technical office hours , that activate developers at VC and accelerator partner events
• Develop a playbook for turning ecosystem touchpoints (builder summits, founder days, VC partnerships) into measurable developer sign-ups and active usage
• Partner closely with the Startups GTM team to create seamless handoffs from relationship → activation → retention

• Create Compelling Technical Content
• Create high-quality technical content , tutorials, demo apps, and blog posts , that showcase how to build real products on Anthropic's API, with a focus on common startup use cases
• Develop code demos and working prototypes that showcase Claude's capabilities in ways that resonate with technical founders, particularly at ecosystem events and webinars
• Partner with the Product team to stay current on platform capabilities and ensure content reflects the latest developer tooling and best practices

• Lead Developer Programming at Startup Events
• Own developer-facing programming at Anthropic's builder summits and global startup activations
• Design and run hands-on technical sessions that move developers from curiosity to active building within a single event
• Build relationships with key technical communities , developer platforms, open-source contributors, and startup accelerator cohorts , to grow Anthropic's developer mindshare
• Represent Anthropic as a trusted technical resource in the startup ecosystem

• Partner Across GTM and Ecosystem
• Surface market signal and developer sentiment from the startup ecosystem back to internal teams
• Partner with GTM, Sales, and Marketing to create developer-focused activation campaigns and messaging for the startup ecosystem
• Work with the Startups Partnerships team to ensure VC and accelerator relationships translate into real developer engagement and usage metrics
• Collaborate closely with the Product team to stay aligned on platform strategy, content, and developer programs

• Define Success and Scale
• Define and track success metrics , tied to net new logos, developer activation, and ecosystem engagement , and build reporting that connects evangelist activity to business outcomes
• Create scalable processes and grow the team as the startup ecosystem expands

Requirements:

• 7+ years of experience across a combination of founding/building startups and developer-facing roles (developer relations, evangelism, or ecosystem development)
• Experience as a technical founder, early startup employee, or operator who has lived the 0-to-1 journey and knows what it takes to go from idea to product-market fit
• The ability to write production-quality code, build compelling demos, and credibly engage with technical co-founders and their engineering teams
• Strong public speaking skills with comfort on stage, the ability to command a room at builder summits and ecosystem events, and deliver technical content that energizes an audience
• Experience building or scaling developer programs, communities, or enablement motions that drove measurable adoption
• Builder credibility that earns trust with founders, VCs, and accelerator communities. You've shipped products and can speak from experience
• Willingness to travel regularly and flexibility to support events that fall outside standard business hours, including evenings and weekends
• Deep enthusiasm for AI with hands-on experience building with LLMs. You stay close to the technology and genuinely care about building it responsibly

Salary Range: $240,000-$315,000 USD

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At Coinbase, our mission is to increase economic freedom in the world.

We're seeking a Data Protection Engineer (L4) to help implement and maintain our data protection capabilities, ensuring the Coinbase ecosystem remains resilient against security threats.

You will contribute to our data protection strategy, helping to balance strong security controls with the speed of a decentralized tech environment.

You will focus on automating data protection operations, utilizing tools including LLMs and agentic AI, to build scalable Data Loss Prevention (DLP) solutions.

You will work with other teams to mitigate risk and ensure compliance with global regulations.

Job Duties:

• Support and expand data loss prevention capabilities to protect Coinbase ecosystem from sophisticated data security incidents
• Support execution of the long term strategy for the Data prevention program to harden security posture against data security threats
• Implement and maintain complex designs/controls across a decentralized tech environment to promote security without impeding the speed of business
• Implement and deploy Data Protection tools and technologies in concert with cross functional teams (ie. endpoint security, information technology, and others)
• Demonstrate operational efficiency across a wide array of DLP Engineering & Operations leveraging LLMs and agentic AI
• Bring an automation first mindset to champion and drive a more streamlined and scalable approach towards DLP operations
• Produce quantitative and qualitative metrics to apprise Data Protection Leadership of programmatic impact and challenges
• Collaborate across Security and Privacy Teams and lead cross functional data protection initiatives
• Collaborate with cross functional teams like engineering, product development, compliance to ensure timely remediation
• Work in concert with risk teams to measure control effectiveness and address changes in laws/regulations globally

Requirements:

• You are an experienced security engineer in the data protection space who can deliver measurable results
• You have the technical acumen to solve operational issues with an engineering solution
• You have direct experience testing, tuning, and implementing data prevention controls across multiple OS stack
• You are comfortable manipulating and orchestrating controls to address multiple operating systems (iOS / Chrome) and decentralized datasets
• You are adept at creating scalable processes, automating where possible, and leveraging ML/AI where feasible to maximize efficiency
• You can be trusted to be discreet and thoughtful while working cross functionally to mitigate risk
• You are actively aware of the insider threat landscape, and understand the legal, regulatory, and ethical considerations of working with sensitive data across a global enterprise
• You have experience working and building Insider Threat technologies (such as Security Information Event Management - SIEM, User Behavioral Analytics - UBA, Data Loss Prevention - DLP) and an understanding of investigations and/or the intelligence cycle
• You have excellent verbal and written communication skills. Other team members ask for your input to communicate clearly and concisely and you are comfortable composing briefs and assessments consumed by leadership
• Business acumen: Proven understanding of business dynamics, goals, and product strategy. Knowledge of how Security fits into Coinbase’s overall business.
• The ability to balance business needs, a sense of urgency, conflicting constraints, and shipping high quality and pragmatic solutions in a fast-moving and quickly-growing company.
• Demonstrates the ability to responsibly use generative AI tools and copilots (e.g., LibreChat, Gemini, Glean) in daily workflows, continuously learn as tools evolve, and apply human‑in‑the‑loop practices to deliver business‑ready outputs and drive measurable improvements in efficiency, cost, and quality.

Nice to Haves:

• 3+ years of security engineering experience solving complex security challenges across enterprise-wide DLP Programs
• Solving operational problems leveraging engineering / automation first mindset
• Experience in Web3 and crypto forward organizations or traditional financial institutions

Experience Level: senior Employment Type: full-time Workplace Type: remote Category: Engineering Industry: Technology Salary Range: $144,500-$170,000 USD Required Skills:

• Experienced security engineer
• Data protection
• LLMs
• Agentic AI
• Data Loss Prevention
• Security Information Event Management
• User Behavioral Analytics
• Insider Threat technologies

Preferred Skills:

• Generative AI tools
• Copilots
• LibreChat
• Gemini
• Glean

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In this role, you will:

Perform manual and automated testing of web applications, APIs, and mobile apps (iOS/Android). Conduct network and cloud level assessments with various tooling. Triage and validate reports from automated scanners or bug bounty hunters to eliminate false positives and escalate true positives. Perform initial prompt injection and jailbreak tests on AI prototypes, services, and applications using established checklists (OWASP Top 10 for LLMs). Draft high-quality reports that detail the "path to compromise" with clear, reproducible steps for developers. Manage and update the team's testing infrastructure (e.g., Burp Suite, and basic C2 listeners). Provide direct technical guidance to engineering teams on how to patch vulnerabilities like XSS, SQLi, and IDOR. Design and lead multi-week Red Team operations that mimic specific threat actors (APTs) to test the SIRT detection capabilities. Build custom payloads, droppers, and obfuscated scripts to bypass EDR/AV and maintain stealth. Build automated testing frameworks for AI systems (e.g., using PyRIT, Promptfoo, or Garak) to test for models related to sensitive data leakage. Execute sophisticated attacks against AWS/Azure/K8s, focusing on IAM misconfigurations and container escapes. Collaborate with SIRT and Detection Engineering to tune SIEM alerts based on the techniques used during an engagement. Oversee the organization's bug bounty program, identifying trends in submissions to suggest broad architectural security changes.

Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply.

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More than 70,000 companies around the globe, including WeWork, Asana, NASDAQ, AAA Insurance, COMPASS Realty, Uber, Randstad, and Tractor Supply, rely on Dialpad to build stronger customer connections using real-time, AI-driven insights.

We’re now leading the shift to Agentic AI: intelligent agents that don’t just analyse conversations but take action by automating workflows, resolving customer issues, and accelerating revenue in real time. Our DAART initiative (Dialpad Agentic AI in Real Time) is redefining what a communications platform can do.

Visit dialpad.com to learn more.

Being a Dialer --------------- AI isn’t just a feature; it’s how our teams do their best work every day. We put powerful AI tools in every employee’s hands so they can move faster, think bigger, and achieve more.

We believe every conversation matters. And we’ve built the platform that turns those conversations into insight and action, for our customers and ourselves.

We look for people who are intensely curious and hold themselves to a high bar. Our ambition is significant, and achieving it requires a team that operates at the highest level.

We seek individuals who embody our core traits: Scrappy, Curious, Optimistic, Persistent, and Empathetic.

Your role -------- As a Sr. SDET in Agentic QA, you will own the test automation and quality frameworks that support Dialpad’s AI Voice Agent services.

You will develop automated tests for end-to-end product experiences, from frontend UI to backend services to APIs to audio/text interactions.

You will test orchestration flows, agent configuration experiences, and guardian safeguards to create robust automated coverage for functionality, performance, reliability, UX, and more.

In this role, you will develop substantial amounts of automated test infrastructure and partner deeply with the development team to make our fast-growing AI platform more testable, more stable, and more delightful for customers.

This position is based at one of Dialpad’s Canadian offices and reports to a QA Eng Manager in the United States.

What you’ll do ------------

• Own end-to-end quality for agentic features and workflows, including strategy, development, execution, and release qualification.
• Design and build automation tooling and frameworks for AI/LLM-driven systems, including prompt flows, agent orchestration, and tool integrations.
• Develop and maintain evaluation frameworks (evals) to measure response quality, accuracy, and hallucination rates.
• Drive automation coverage (80%+ for critical AI workflows) using deterministic + probabilistic validation approaches.
• Integrate AI quality checks into CI/CD pipelines with fast feedback cycles (
• Build tooling for LLM observability and debugging, including prompt tracing and response analysis.
• Partner with Applied AI teams on prompt engineering, model selection, and evaluation strategies.
• Design and execute performance and load tests for AI services (latency, throughput, cost efficiency).
• Identify and mitigate risks related to hallucinations, bias, safety, and edge cases.
• Define and track AI quality KPIs (task success rates, precision/recall, latency, etc.).
• Participate in design and architecture reviews to ensure systems are testable, observable, and resilient.
• Mentor engineers and contribute to raising the bar on AI quality engineering practices.

What you’ll bring --------------

• 5+ years of experience in software engineering or SDET roles with an emphasis on software development.
• Strong programming skills in Python (preferred), Java, or JavaScript.
• Experience testing distributed, cloud-native SaaS systems and APIs.
• Demonstrated proficiency in coding with AI agents to accelerate development and improve code quality.
• Hands-on exposure to LLMs or AI/ML systems (e.g., OpenAI, Claude, Gemini, or similar platforms).
• Understanding of non-deterministic systems and probabilistic testing approaches.
• Experience building test frameworks and scalable automation systems.
• Familiarity with AI evaluation techniques (benchmarking, golden datasets, human-in-the-loop validation).
• Experience with CI/CD pipelines (e.g., Jenkins, GitHub Actions).
• Strong collaboration skills with the ability to work across distributed teams and time zones.
• Bachelor’s degree in Computer Science or equivalent practical experience.

Backend: Python, Go, Google Cloud Platform, Cloud Run / App Engine, Kubernetes, Datastore, Redis, ElasticSearch.

• Frontend: Vue3, React.
• AI Stack: LLM APIs, LiveKit, prompt orchestration frameworks, evaluation tooling.

For exceptional talent based in British Columbia, Canada the target base salary range for this position is $150,500-$175,250 CAD.

Why Join Dialpad ---------------

• Work at the center of the AI transformation in business communications.
• Build and ship agentic AI products that are redefining how companies operate.
• Join a team where AI amplifies every employee’s impact.
• Competitive salary, comprehensive benefits, and real opportunities for growth.

We believe in investing in our people. Dialpad offers competitive benefits and perks, cutting-edge AI tools, and a robust training program that help you reach your full potential.

We have designed our offices to be inclusive, offering a vibrant environment to cultivate collaboration and connection.

Our exceptional culture, repeatedly recognized as a Great Place to Work, ensures that every employee feels valued and empowered to contribute to our collective success.

Don’t meet every single requirement? If you’re excited about this role and possess the fundamental traits, drive, and strong ambition we seek, but your experience doesn’t meet every qualification, we encourage you to apply.

Dialpad is an equal-opportunity employer. We are dedicated to creating a community of inclusion and an environment free from discrimination or harassment.

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This person will partner closely with Sales Enablement, Revenue Operations, Sales Leadership, Product Marketing, and People teams to ensure new hires are ramped quickly, consistently, and confidently on CoreWeave's products, customers, and sales motions.

Key responsibilities include:

• Owning the GTM Onboarding Program
• Designing, documenting, and maintaining standardized onboarding journeys by role (SDR, AE, Sales Leadership, SE, CSM, etc.)
• Defining clear milestones, certifications, and success criteria for new hires (e.g., pitch certification, discovery certification, first opportunity created/closed)
• Partnering with managers to align onboarding outcomes with territory plans and performance expectations

Program Delivery & Coordination

• Building and managing onboarding calendars, live sessions, and office hours in partnership with functional experts
• Facilitating or co-facilitating sessions on CoreWeave story, product portfolio, sales process, tools, and best practices
• Ensuring logistics (invites, recordings, materials, follow-up tasks) are coordinated and executed with high reliability

Content & Resource Management

• Curating and maintaining onboarding paths and resources in Confluence and other internal systems, ensuring information is accurate, structured, and easy to navigate
• Partnering with content owners to ensure onboarding materials are updated following major product launches, process changes, or tool rollouts

Measurement & Continuous Improvement

• Defining and tracking onboarding KPIs such as time-to-first-meeting, time-to-first-opportunity, and time-to-first-win
• Analyzing feedback and performance data to identify bottlenecks and iterate on content, format, and sequencing
• Regularly reporting onboarding performance and insights to Sales Enablement leadership and GTM leaders

New Hire Experience & Communication

• Serving as a primary point of contact for new hires throughout their initial ramp period, ensuring a smooth and consistent experience
• Providing proactive communications to new hires and their managers on expectations, schedules, and required pre-work
• Partnering with People team to ensure onboarding is aligned with CoreWeave's culture and values

Alignment with Broader Enablement

• Coordinating handoffs from onboarding into ongoing enablement programs and recurring training sessions
• Ensuring onboarding themes and skills (pitching, discovery, objection handling) ladder into the broader enablement roadmap

Key Qualifications

• Experience: 3–5 years in sales enablement, onboarding, L&D, or GTM operations, preferably in a SaaS or technology environment
• Program Design: Demonstrated experience architecting and running structured onboarding or training programs at scale
• Communication: Excellent written and verbal communication skills with a focus on clarity, conciseness, and storytelling
• Organization: Strong project management skills with the ability to manage multiple cohorts, timelines, and stakeholders simultaneously
• Technical Proficiency: Comfortable with sales and enablement tools (e.g., CRM, Gong, LMS, LinkedIn Sales Navigator, Confluence)
• Collaboration: Proven ability to work cross-functionally with sales, marketing, product, RevOps, and People teams to drive outcomes
• Proactive & Detail-Oriented: Track record of owning programs end-to-end and sweating the details from invites to follow-ups

Experience Level: Mid

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Key responsibilities include:

Defining the vision and strategy for PLM across the enterprise Setting goals, policies, and processes that guide how PLM customization and integration work gets done company-wide Managing a department of developers, solution engineers, and technical leads Building and scaling high-performing teams Overseeing workforce planning and budget allocation across multiple programs Creating career frameworks, technical standards, and engineering practices Driving architectural decisions that impact PLM infrastructure, integrations, and scalability for the entire organization Partnering with senior leadership across Engineering, Operations, IT, and Product to align PLM strategy with company priorities Communicating technical strategies to C-suite audiences Overseeing multi-million dollar budgets for PLM licensing, infrastructure, and team operations Ensuring business continuity and operational excellence

The ideal candidate will have 8+ years of engineering experience, with at least 4+ years in people management, including 2+ years managing managers or leading multiple teams. They will also have expertise in Enterprise PLMs, including architecture, customization, and integrations, as well as broad understanding of enterprise systems landscape.

In addition to the required qualifications, preferred qualifications include experience in defense, aerospace, or highly regulated manufacturing environments at scale, background implementing Teamcenter at a company during hypergrowth, prior experience in startup or high-growth technology companies, and track record of successful M&A integrations or large-scale system migration.

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Responsibilities:

• Develop and manage comprehensive project plans to execute on initiatives, identify key milestones, and ensure alignment across stakeholders
• Think both broadly about overall outcomes while using good judgment on where to focus in on details
• Influence the technical direction of projects to meet the stakeholders' needs while upholding quality
• Quickly validate project ideas through iterative development, and pivot as necessary
• Define and align on success criteria for both short-term and long-term business goals, regularly assessing risks and opportunities and identifying mitigation strategies
• Manage effective communication channels to keep a wider range of stakeholders updated on the progress
• Showcase the work in front of senior leaders, clearly communicate trade-offs, risks, and opportunities

Your Expertise:

• 7+ years of experience in the software development industry, with at least 5 years as a TPM or relevant experience
• Experience using AI to automate manual processes to improve you and your team's productivity
• Demonstrated ability to work through ambiguity to detailed solutions
• Self-motivated, proactive, and proven ability to adapt well and work with teams having different operating cadences
• Sound business judgment, a proven ability to influence others, strong analytical skills, and a track record of taking ownership, leading data-driven analyses, and influencing results
• Experience with ML models, LLMs, LRMs, feature development, model testing, and resource management to support the development of AI-powered product experiences
• Familiar with A/B testing, incremental delivery, and deployment
• Ability to ramp up quickly and learn new technologies with minimal lag time
• Excellent written and oral business communication and people skills, with the ability to influence stakeholders

Nice to have:

• Experience developing or working directly on various aspects of large-scale ML/AI platforms
• Experience with feature development of AI-powered product experiences
• Experience and passion for building and maintaining products leveraging AI models

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At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world's largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies.

We protect and accelerate any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks.

About the Team

The GTM Developer team is a startup within Cloudflare, driving the go-to-market strategy for our developer products and shaping the future of application development. We are at the forefront of a fundamental shift in how developers build, particularly with the rise of AI and LLMs.

What you'll do

We are seeking an engineering leader with an entrepreneurial mindset to guide our Developer Adoption team. This is not a traditional developer relations role. We're looking for a former VP of Engineering, CTO, or a similar leader who has built things and understands the developer journey from the inside out.

You will be tasked with iteratively defining the future of your own role and the function itself, translating market signals into a strategic, evolving organization. In this role, you will:

• Provide the vision and engineering leadership to redefine how Cloudflare engages with the developer community in the age of AI.
• Lead and mentor our existing high-performing team of developer advocates, educators, and community managers, guiding their evolution and impact.
• Operate with 'startup energy',acting with autonomy and hunger to carry significant responsibility and drive our developer GTM strategy.
• Champion the developer experience, engaging with peers across Product and Engineering to translate community feedback into a world-class platform.
• Act as a key evangelist and storyteller, articulating a compelling and optimistic vision for the future of development on Cloudflare.
• Cultivate a passionate, hard-working, and collaborative culture, inspiring your team to overcome challenges and innovate.

Examples of desirable skills, knowledge and experience

We are looking for a leader who is more of a founder than a function manager. Your passion, optimism, and ability to build are more important than a traditional career path in developer relations.

• Proven experience in a senior engineering leadership role (e.g., VP of Engineering, CTO), having built and scaled products and teams.
• An entrepreneurial spirit and 'startup energy,' with a history of building things, whether in a successful venture or a passionate side project.
• A deep empathy for developers and an understanding of the fundamental shifts happening in technology, especially around AI and LLMs.
• Exceptional storytelling ability with the passion and excitement to inspire both internal teams and the external developer community.
• The ability to thrive in a highly autonomous environment, comfortable with ambiguity and defining your own path forward.
• A genuine optimism and resilience to navigate challenges and lead with a can-do attitude.

Compensation: Compensation may be adjusted depending on work location. For San Francisco Bay Area based hires: Estimated annual salary of $299,000 - $365,000

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The ISD will collaborate closely with the Senior Manager of Training Operations, Curriculum Developer, and Subject Matter Experts (SMEs) to operationalize training content into systems and structures that enable seamless delivery and accessibility for diverse end-user audiences. As a key partner in training lifecycle, the ISD will help design the “how” of training delivery with a focus on scalability, effectiveness, and system performance.

Systems Design & Implementation:

• Design and implement scalable instructional systems, frameworks, and processes to deliver highly technical training content (e.g., LMS platforms, SCORM-compliant systems, virtual training platforms, or other performance support tools).
• Develop innovative approaches to operationalizing technical training, optimizing delivery methods while working within the constraints of Air Force or other military standards and regulations.
• Test and validate system performance to ensure seamless integration of training content developed by Curriculum Developers.
• Conduct usability testing to ensure systems meet the needs of end-users, including engineers, pilots, maintainers, and government clients.

Stakeholder Collaboration:

• Work with the Senior Manager of Training Operations, SMEs, and Curriculum Developers to design, implement, and scale training solutions that align with organizational objectives and military standards.
• Act as the strategic bridge between content creation teams and systems implementation, ensuring that what is created by Curriculum Developers aligns with how it is delivered.
• Build strong collaborative relationships across business lines, technical teams, and external clients, serving as a trusted advisor on training systems' design and optimization.

Needs Analysis & Delivery Innovation:

• Conduct thorough training needs analyses to identify optimal systems or platforms for specific training goals based on the needs of diverse learners and stakeholders.
• Leverage expertise in industry standards and emerging technologies (e.g., SCORM-compliant tools, LMS platforms, AR/VR solutions, or AI-driven training platforms) to recommend and implement cutting-edge instructional systems.
• Align delivery methods with military or government standards, ensuring innovative, forward-thinking solutions are still compliant with required frameworks and policies.

Evaluation & Optimization:

• Develop methods to monitor and report on system and learner performance, using LMS data, analytics dashboards, and evaluation models (e.g., Kirkpatrick’s Levels of Evaluation).
• Analyze data to refine implementation strategies, improve training effectiveness, and adapt to changing requirements.
• Partner with stakeholders to provide insights on how training systems contribute to performance outcomes and organizational objectives in technical or military contexts.

Standardization & Compliance:

• Ensure all training systems and their implementation comply with military standards (e.g., Air Force training specifications), organizational policies, and industry benchmarks such as SCORM or xAPI.
• Maintain consistent documentation of systems processes, best practices, and lessons learned to create scalable, repeatable training system operations.
• Stay up-to-date on emerging military and government compliance requirements for training systems.

Required Qualifications:

• Bachelor’s degree in Instructional Design, Systems Engineering, Educational Technology, or a related field.
• 5+ years experience as an Instructional Systems Designer or similar role, with demonstrated success in designing scalable frameworks for technical, engineering, aerospace, or defense-related environments.
• Familiarity with Air Force or other U.S. military training programs, including their standards and operational constraints, is required.
• Strong collaboration and communication skills, with the ability to build trust and work effectively in a matrixed and high-stakes environment.
• Analytical thinking and problem-solving skills, with a focus on delivering innovative solutions while balancing organizational constraints.
• Proficiency with e-learning authoring tools (e.g., Articulate Storyline, Adobe Captivate) and multimedia production tools.
• Knowledge of systems integration standards and frameworks, including SCORM, xAPI, or cmi5 compliance.
• Ability to manage multiple projects in a fast-paced, ambiguous environment.

Preferred Qualifications:

• Experience supporting Group 5 UAS, FAA Part 145 MRO, production test, flight test environments, or highly technical/regulated industries.
• Understanding of Learning Management Systems (LMS) and training tracking tools (e.g., Cornerstone).
• Relevant certifications, such as CPLP, Agile Practitioner, or instructional design/technology credentials.
• Familiarity with immersive technologies, such as VR/AR, and their applications in training design and implementation.
• Experience with Agile workflows or project management tools like Jira.
• Prior Military experience (Operations or Maintenance Officer/Senior Enlisted).

US Salary Range: $98,000-$130,000 USD

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At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world's largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies.

As a Solutions Engineer Intern, you'll join Cloudflare's APAC Solutions Engineering, Center of Excellence (COE) team as part of a small cohort of interns working directly with the team running an internal AI initiative. The goal is to build AI capabilities across SE, Sales, and GTM functions in APAC.

Responsibilities

• Build and test an AI agent or internal chatbot to help SE and Sales teams work faster, built on Cloudflare Workers AI and AI Gateway
• Design and prototype a demo that shows Cloudflare's AI platform capabilities for a real customer use case
• Write scripts or lightweight tools that cut manual work out of GTM workflows
• Dig into usage or productivity data to see what impact the tools your team built are actually having
• Present your work at a team showcase or sprint review

Success Looks Like

• Ship at least one internal AI tool that SE or GTM colleagues are actively using
• Contribute to tools or demos that make a real difference to how the team works
• Leave with at least one piece of work the wider team can pick up and use

Requirements

• Can write working code in Python, JavaScript, or a similar language and ship things independently
• Have a basic understanding of how the web works: HTTP, REST APIs, DNS, TLS
• Can explain what you built and why, to a technical or non-technical audience
• Are curious and self-directed. You try things before asking
• Able to commit to a minimum 12 week summer internship from May to August 2026
• Able to work from office 3-5 days a week in Singapore

It would be awesome if you also:

• Have played around with LLMs, AI APIs, or prompt engineering, even just in side projects, coursework, or a hackathon
• Have used any part of the Cloudflare developer platform: Workers, R2, Pages, or anything similar
• Have experience with data analysis or lightweight dashboarding (Python, notebooks, etc.)
• Have shipped something as part of a team: a university capstone, hackathon project, open source contribution, or a previous internship

Technologies we work with

Cloudflare Workers, Workers AI, AI Gateway, Vectorize, Pages, R2, D1, KV · Python · JavaScript / TypeScript

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Responsibilities:

• Collaborate with AI platform developers, security architects, and internal stakeholders to distill feature asks, gather feedback, and ensure product-market fit for AI agent identity.
• Define and own the product strategy and roadmap for AI agent-specific capabilities, including agent-to-agent authentication and delegated authority.
• Identify and prioritize the development of new features such as dynamic session management for AI, "on-behalf-of" token exchange, and agent-specific audit logs.
• Work closely with engineering and architecture teams to define protocols (e.g., extensions to OAuth/OIDC) and deployment models that align with modern AI orchestration frameworks.
• Drive cross-functional execution with design, engineering, and documentation teams to deliver high-quality features on time.
• Track industry trends in LLMs, agentic frameworks (e.g., LangChain, AutoGPT), and emerging AI security standards to develop differentiated solutions.
• Leverage product data to continually improve agent lifecycle management and drive adoption within the developer community.
• Serve as the subject matter expert for AI Identity, enabling marketing and technical sales teams with the tools needed to position Okta for AI use cases.

Required Experience:

• 5+ years of technical product management experience in enterprise-scale SaaS products, or an equivalent background demonstrating core PM competencies.
• Strong knowledge of Identity and Access Management (IAM) protocols such as OAuth2, OIDC, and SAML.
• Hands-on experience with AI/ML frameworks or building products that leverage Large Language Models (LLMs).
• Analytical and decisive: Ability to drive action even with incomplete or ambiguous information in the rapidly evolving AI landscape.
• Excellent communication skills: Ability to work cross-functionally with research, design, engineering, and customer success teams.
• Technical background: Bachelor’s degree in Computer Science, Computer Engineering, or equivalent experience that allows you to influence technical design decisions.

Preferred Experience:

• Experience with developer-centric products, such as building with SDKs, APIs, or no-code/low-code integration platforms.
• Familiarity with Zero Trust architecture and how it applies to non-human entities and automated workloads.
• Prior experience in a "Zero to One" product environment, launching new products from initial concept to GA.
• Advanced degree in a technical or business field.

Annual Salary Range: $146,000-$200,000 CAD

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Senior Software Engineer, AI Products (India)

Company Overview

Airbnb is a global online marketplace for booking accommodations, with over 5 million hosts and 2 billion guest arrivals.

The Community You Will Join

The Airfam Products team exists to make every Airbnb employee more productive through a unified digital headquarters experience. As part of a 13-person cross-functional team of engineers, designers, researchers, and product managers, you'll work on platforms that serve Airbnb's entire global workforce. Our portfolio includes One Airbnb (the company's internal cultural hub with enterprise search, people profiles, and AI-powered chat), OneChat (Airbnb's enterprise AI assistant enabling secure LLM interactions), and a suite of tools that power how employees discover information, connect with colleagues, and get work done. You'll be joining the AI for Non-Developers workstream, focused on expanding AI productivity tools to all Airbnb employees,building OneChat Agents, deep research capabilities, artifact creation tools, and task automation that make AI accessible to everyone, regardless of technical background.

The Difference You Will Make

As a Senior Software Engineer on the Airfam Products team, you'll be instrumental in building Airbnb's next generation of AI-powered employee experience platforms. Your work will be a force multiplier for the entire company,every AI feature you ship, every system you architect, and every engineer you mentor will amplify productivity across Airbnb's global workforce. You will:

• Democratize AI by building tools that empower non-technical employees to leverage the power of LLMs
• Drive innovation by taking AI prototypes from concept to production at scale
• Shape the future of how Airbnb employees work, collaborate, and discover information

A Typical Day

• Lead the technical design and implementation of LLM-powered features for OneChat and enterprise AI tools, including RAG pipelines, AI agents, and prompt optimization
• Partner with product managers, designers, and cross-functional teams to translate user problems into AI-powered solutions that serve Airbnb's global workforce
• Develop and iterate on agentic AI capabilities, including multi-step reasoning, tool use, and context-aware decision-making
• Implement evaluation pipelines and quality systems to measure model performance, detect hallucinations, and ensure responsible AI practices
• Own production AI systems end-to-end, including deployment strategies, monitoring, alerting, and incident response
• Collaborate with the DevAI team on AirChat SDK integrations, MCP (Model Context Protocol) implementations, and Glean Action Packs
• Mentor engineers (L6-L8) through design reviews, architecture discussions, and pair programming sessions
• Stay current with the rapidly evolving GenAI landscape, evaluating new models and techniques for potential application
• Balance hands-on technical contributions with technical leadership activities

Your Expertise

• 8+ years of software engineering experience, with significant focus on building production AI/ML systems
• 2+ years of hands-on experience with Large Language Models (LLMs), including fine-tuning, prompt engineering, embeddings, and retrieval-augmented generation (RAG)
• Strong proficiency in backend technologies (TypeScript, Go, or Java)
• Strong backend and distributed systems expertise, including API design (REST, GraphQL) and cloud infrastructure (AWS, GCP, or Azure)
• Track record of shipping AI-powered products from prototype to production
• Proven ability to collaborate cross-functionally and influence without authority
• Excellent communication skills with ability to distill complex technical concepts for diverse audiences
• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience

Preferred

• Master's or PhD in Computer Science, Machine Learning, or related field
• Experience building AI agents and multi-agent systems, preferably using Claude
• Experience building integrations using MCP
• Experience with containerization and orchestration (Docker, Kubernetes)
• Background in building enterprise-grade internal tools and developer productivity platforms
• Experience with frontend technologies (React, Next.js) for full-stack AI product development
• Contributions to open-source Gen AI/ML projects or publications at top venues

Your Location

This position is based in Bangalore, India with a hybrid work arrangement. You'll collaborate with teammates across global time zones, with primary alignment to Pacific Time for key meetings.

Our Commitment to Inclusion & Belonging

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.

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You will set the technical direction, write code and ship tooling alongside your team, and build the culture and processes that allow the team to scale.

Corporate Security at Anthropic encompasses everything that protects our people, endpoints, networks, SaaS ecosystem, and corporate data,the full surface area outside of production infrastructure.

The scope is broad and the team is deliberately small, which means you'll need deep technical skills across multiple domains, strong judgment about where to invest, and a bias toward automation and engineering-driven solutions over manual process.

You'll report into Security leadership and partner closely with IT, Infrastructure Security, Detection & Response, and GRC teams.

This role is high-visibility and high-autonomy: you'll be expected to define the roadmap, make architectural decisions, and represent Corporate Security across the company.

Responsibilities:

Technical Leadership & Hands-on Engineering

• Own the security architecture, tooling, and controls for Anthropic's corporate environment end-to-end, including endpoint fleets (macOS, Windows, ChromeOS), campus and office networks, SaaS applications, mobile devices

• Design, build, and ship security automation, integrations, and internal tooling,including leveraging Claude and LLMs to accelerate security workflows

• Define and enforce security baselines, hardening standards, and configuration policies across all corporate platforms

• Define what it means to operate safely in an environment where AI agents act more like humans than actual humans

• Evaluate, select, deploy, and operate corporate security tools (EDR/XDR, MDM, ZTNA, CASB/SSPM, email security, DLP, browser security, etc.)

• Drive vulnerability management for corporate assets, including patch orchestration, risk-based prioritization, and exception management

• Lead security reviews of new SaaS adoptions, corporate infrastructure changes, and IT projects

People Leadership & Team Building

• Manage, mentor, and grow a purposefully lean team of Security Engineers; set clear expectations, run effective 1:1s, and create an environment where engineers do the best work of their careers

• Hire and build the team as scope expands,own the hiring bar and pipeline for Corporate Security Engineering roles

• Balance your own IC contributions with the team’s needs; know when to go deep on a problem yourself and when to delegate and coach

• Foster a culture of operational excellence, blameless incident review, and continuous improvement

Strategy & Cross-Functional Partnership

• Define and own the Corporate Security roadmap, aligning investments to Anthropic’s risk profile and growth trajectory

• Partner with IT Operations to ensure security is embedded in endpoint provisioning, network design, and SaaS lifecycle management

• Collaborate with Detection & Response on telemetry coverage, detection engineering, and incident handling for corporate-sourced events

• Partner with Infrastructure and Security Engineering teams to ensure security standards are consistent across all of Anthropic

• Communicate security posture, risks, and investment needs to Security leadership and cross-functional stakeholders clearly and persuasively

Requirements

• 8+ years of Security Engineering experience in a corporate/enterprise security domain (endpoint security, network security, SaaS security, identity, or a combination)

• 2+ years of experience managing or tech-leading a team of engineers, with a demonstrated track record of developing talent and shipping results through others

• Are a strong engineer who still writes code regularly,you can prototype a tool, write a detection, build an integration, or debug a complex configuration issue

• Have deep experience with macOS fleet security (this is our primary platform) and solid working knowledge of Windows and ChromeOS security

• Have hands-on experience deploying and operating EDR/XDR, MDM, ZTNA/zero trust, and identity security solutions at scale

• Understand modern SaaS security challenges: shadow IT, OAuth token sprawl, data exfiltration paths, SaaS-to-SaaS integrations, and SSPM/CASB tooling

• Can work independently with high autonomy, manage ambiguity, and make sound risk-based prioritization decisions in a fast-paced environment

• Have excellent communication skills and can translate complex security topics into clear recommendations for technical and non-technical audiences

Strong Candidates May Have

• Securing corporate environments at high-growth AI, cloud, or developer-tools companies

• Maturing a Corporate Security function from early stage, including defining scope, selecting the initial toolset, and hiring the founding team

• Advanced macOS security (system extensions, endpoint security framework, MDM profile engineering, Declarative Device Management)

• Network security architecture for hybrid/multi-office environments, including SD-WAN, ZTNA, DNS security, and network segmentation

• Browser security and isolation technologies (e.g., Island, Talon/Palo Alto, Chrome Enterprise)

• Proficiency in Python, Go, or similar languages for building security tooling and automation

• Experience leveraging LLMs/AI to augment security operations, build investigative tooling, or automate policy enforcement

• Familiarity with IaC (Terraform), CI/CD pipelines, and DevSecOps practices as they apply to corporate infrastructure management

• Mobile security for iOS/Android in a BYOD and corporate-managed device environment

• Data Loss Prevention (DLP) program design and implementation across endpoints, email, SaaS, and cloud storage

Logistics

• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

• Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

• Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

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You'll partner closely with Brand, Marketing, and Product Design to translate complex technical stories into sharp, high-quality visual communication, and you'll help us move faster by introducing modern AI-assisted creative workflows that the whole team can adopt.

Key responsibilities include:

• Design and ship marketing assets across channels,blog graphics, social, ads, landing-page assets, one-pagers, templates, collateral and more.
• Create and maintain a repeatable, on-brand system for output (templates, reusable components, and lightweight guidelines) so quality scales with volume.
• Partner with stakeholders to critique and refine briefs (not just execute them),clarifying goals, tightening scope, and improving upstream inputs over time.
• Bring options and rationale (not just files): share 2–3 strong directions and explain tradeoffs.

We're looking for a 5+ year experienced brand/visual designer with strong static-first craft, a portfolio showing high-quality work, and proven ability to use AI tools to increase creative throughput.

Additional requirements include proficiency in Figma and the Adobe suite, familiarity with modern creative AI tooling, and willingness to learn Alchemy's product suite deeply.

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When you see what modern language models are capable of, do you wonder, "How do these things work? How can we trust them?" The Interpretability team at Anthropic is working to reverse-engineer how trained models work because we believe that a mechanistic understanding is the most robust way to make advanced systems safe.

We're looking for researchers and engineers to join our efforts. People mean many different things by "interpretability". We're focused on mechanistic interpretability, which aims to discover how neural network parameters map to meaningful algorithms.

A few places to learn more about our work and team at a high level are this introduction to Interpretability from our research lead, Chris Olah; a discussion of our work on the Hard Fork podcast produced by the New York Times, and this blog post (and accompanying video) sharing more about some of the engineering challenges we’d had to solve to get these results.

Some of our team's notable publications include A Mathematical Framework for Transformer Circuits, In-context Learning and Induction Heads, Toy Models of Superposition, Scaling Monosemanticity, and our Circuits’ Methods and Biology papers.

This work builds on ideas from members' work prior to Anthropic such as the original circuits thread, Multimodal Neurons, Activation Atlases, and Building Blocks.

We aim to create a solid foundation for mechanistically understanding neural networks and making them safe (see our vision post).

In the short term, we have focused on resolving the issue of "superposition" (see Toy Models of Superposition, Superposition, Memorization, and Double Descent, and our May 2023 update), which causes the computational units of the models, like neurons and attention heads, to be individually uninterpretable, and on finding ways to decompose models into more interpretable components.

Our subsequent work found millions of features in Sonnet, one of our production language models, represents progress in this direction.

In our most recent work, we develop methods that allow us to build circuits using features and use this circuits to understand the mechanisms associated with a model's computation and study specific examples of multi-hop reasoning, planning, and chain-of-thought faithfulness on Haiku 3.5, one of our production models.

This is a stepping stone towards our overall goal of mechanistically understanding neural networks.

We often collaborate with teams across Anthropic, such as Alignment Science and Societal Impacts to use our work to make Anthropic’s models safer.

We also have an Interpretability Architectures project that involves collaborating with Pretraining.

Responsibilities

• Develop methods for understanding LLMs by reverse engineering algorithms learned in their weights
• Design and run robust experiments, both quickly in toy scenarios and at scale in large models
• Create and analyze new interpretability features and circuits to better understand how models work.
• Build infrastructure for running experiments and visualizing results
• Work with colleagues to communicate results internally and publicly

You may be a good fit if you:

• Have a strong track record of scientific research (in any field), and have done some work on Interpretability
• Enjoy team science – working collaboratively to make big discoveries
• Are comfortable with messy experimental science. We're inventing the field as we work, and the first textbook is years away
• You view research and engineering as two sides of the same coin. Every team member writes code, designs and runs experiments, and interprets results
• You can clearly articulate and discuss the motivations behind your work, and teach us about what you've learned. You like writing up and communicating your results, even when they're null

To learn more about the skills we look for and how to prepare for this role, see our blog post – So You Want to Work in Mechanistic Interpretability?

Familiarity with Python is required for this role.

Role Specific Location Policy:

• This role is based in San Francisco office; however, we are open to considering exceptional candidates for remote work on a case-by-case basis.

The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Annual Salary: $350,000-$850,000 USD

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As one of the first engineers in the NYC Engineering office, you'll have the opportunity to be part of a small, nimble team that's innovating to build new products from the ground up.

Our goal is to leverage the power of Databricks in data & AI to deliver vertical AI applications for both technical and business users.

The impact you'll have:

• Create novel, never-seen-before interfaces for GenAI agents that manage complex workflows while keeping the human in the loop through inspectability and transparency
• Partner closely with product management, design, and other engineering teams to build intuitive, scalable, and extensible solutions that drive user & business growth
• Lead by example with hands-on full-stack software development to create dynamic, user-centric experiences
• Enable mechanisms that can drive product-led growth, through seamless onboarding and sharing capabilities
• Direct the future of intuitive agentic applications at Databricks, in collaboration with cross-functional teams of innovative software engineers, product managers, and designers
• Define and drive the strategy for building end-to-end AI feature development by designing, building, and maintaining systems that are scalable, reliable, and performant.

What we look for:

• 10+ years of experience with HTML, CSS, and JavaScript
• Demonstrated product mindset with the ability to translate ambiguous customer problems into scrappy MVPs and iterate quickly based on data and user feedback.
• You care that AI features feel intuitive, trustworthy, and helpful, not just bolted on to an existing app
• High ownership and bias for action in 0→1 environments: you are comfortable making pragmatic trade-offs, operating with incomplete information, and driving projects from idea through launch and adoption.
• Strong ability to collaborate across product, engineering, and design teams to align technical strategy with company growth objectives.
• Experience with modern JavaScript frameworks (e.g., React, Angular, or VueJs/Ember)
• 10+ years of experience with server-side web technologies (eg: Node.js, Java, Python, Scala, C#, C++,Go)
• Proven experience building and shipping end-to-end generative AI products, ideally with a significant UI/UX component
• Proven experience building and shipping end-to-end generative AI products
• Deep familiarity with LLMs and generative AI, including hands-on experience with techniques like retrieval-augmented generation (RAG), prompt design, evaluation, and monitoring AI quality and safety in production.

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As a Staff Engineer, AI Security on the AppSec team, you'll lead autonomous defense for the AI lifecycle. Build multi-agent frameworks and secure gateways while integrating real-time security gates and identity standards. By mentoring Security and R&D to define the MLSecOps roadmap, you'll ensure a 'secure-by-default' future for agentic workflows and resilient AI innovation.

Responsibilities:

Serve as the primary subject matter expert for all AI and machine learning security initiatives across security and R&D.

Design and manage AI gateways to provide a centralized control plane for authentication and authorization and rate limiting across all model and tool interactions.

Build and maintain an autonomous security agentic framework that utilizes multi agent orchestration for end to end investigation and alert triage and remediation.

Develop agentic identity models using OAuth 2.1 to propagate identity across trust boundaries and prevent the confused deputy problem.

Help govern the AI augmented software development lifecycle by integrating real time security gates into the developer environment and CI/CD pipeline.

Manage Agentic Security Solutions that secure AI lifecycle and manage AI workloads at runtime.

Author company wide AI security standards and implement these security checks across Twilio's stack.

Implement human in the loop checkpoints and transactional safety protocols for high impact or destructive agentic actions.

Partner with engineering leadership to set the long term roadmap for identity centric security and automated posture management.

Act as a knowledge multiplier by mentoring security engineers and developing secure by default paved road templates for R&D teams

Qualifications:

8+ years of experience in security engineering with at least 3 years focused on AI or machine learning security operations (MLSecOps).

Expertise in orchestrating multi-agent systems with AWS Strands, LangGraph, and CrewAI, specializing in runtime isolation, PII redaction, and defending against indirect prompt injection in agentic environments.

Hands-on experience with AI-specific frameworks (e.g., MITRE ATLAS, MAESTRO, OWASP Top 10 for LLMs/Agents/MCP) to threat model and defend against a wide spectrum of risks, including direct/indirect prompt injection, training data poisoning, tool poisoning, and data exfiltration within agentic workflows.

Proficiency in securing end-to-end AI pipelines, from data ingestion and training to model deployment and monitoring.

Strong communication skills to translate complex AI risks into actionable business logic for stakeholders.

Desired:

Hands-on experience in modern application security tooling including SAST and SCA and DAST with experience adapting these tools to catch AI specific vulnerabilities like indirect prompt injection.

Expertise in identity standards including OAuth 2.1 and PKCE.

Experience with AI Red Teaming and conducting adversarial simulations against Large Language Models (LLMs) and agentic systems.

Proficiency in at least one general programming language (Python, Go, etc) with experience in container security and workload isolation.

Proven ability to operate with autonomy and drive high impact outcomes in ambiguous environments by identifying and executing on critical projects without predefined roadmaps or direct supervision.

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You will systematically identify high-priority behavioural improvements, coordinate across Research, Product, and Safeguards teams, and accelerate our ability to ship well-aligned models.

Key responsibilities include defining behavioural defaults and steerability constraints, developing and maintaining taxonomies of model behaviours across capabilities, identifying, triaging, and prioritising behaviour issues and opportunities, and amplifying alignment research breakthroughs.

To succeed in this role, you will need to have a deep passion and curiosity for AI and LLMs, a track record of delivering products and features to end-users, strong user empathy and the ability to synthesise vague or contradictory feedback into actionable priorities, and a strong grasp of ML concepts.

The ideal candidate will be a first-principles thinker with the ability to navigate and execute amidst ambiguity, flexing into different domains based on the business problem at hand and finding simple, easy-to-understand solutions.

This role offers a competitive compensation range of $305,000-$385,000 USD per year, with a minimum education requirement of a Bachelor's degree or an equivalent combination of education, training, and/or experience.

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In the last year, we've seen compelling signs that LLMs and agents are increasingly capable of novel cyber capabilities. We think 2026 will be the year where models reach expert-level, even superhuman, in several cybersecurity domains. This is a novel and massive threat surface.

As a Research Scientist on FRT focusing on cyber, you'll build the tools and frameworks needed to defend the world against advanced AI-enabled cyber threats. Senior candidates will have the opportunity to shape and grow Anthropic's cyberdefense research program, working with Security, Safeguards, Policy, and other partner teams.

This work sits at the intersection of AI capabilities research, cybersecurity, and policy,what we learn directly shapes how Anthropic and the world prepare for AI-enabled cyber threats. This is applied research with real-world stakes. Your work will inform decisions at the highest levels of the company, contribute to demonstrations that shape policy discourse, and build the technical defenses that we will need for a future of increasingly powerful AI systems.

Responsibilities

• Develop systems, tools, and frameworks for AI-empowered cybersecurity, such as autonomous vulnerability discovery and remediation, malware detection and management, network hardening, and pentesting
• Design and run experiments to elicit and evaluate autonomous AI cyber capabilities in realistic scenarios
• Design and build infrastructure for evaluating and enabling AI systems to operate in security environments
• Translate technical findings into compelling demonstrations and artifacts that inform policymakers and the public
• Collaborate with external experts in cybersecurity, national security, and AI safety to scope and validate research directions

Sample Projects

• Building frameworks and tools that enable AI models to autonomously find and patch vulnerabilities
• Running purple-team simulations where AI defenders compete against AI attackers in network environments
• Pointing autonomous AI systems at real-world security challenges (bug bounties, CTFs etc.) to characterize risks, defensive potential, and compare to human experts
• Building demonstrations of frontier AI cyber capabilities for policy stakeholders

You May Be a Good Fit If You

• Have deep expertise in cybersecurity or security research
• Are driven to find solutions to complex, high-stakes problems
• Have experience doing technical research with LLM-based agents or autonomous systems
• Have strong software engineering skills, particularly in Python
• Can own entire problems end-to-end, including both technical and non-technical components
• Design and run experiments quickly, iterating fast toward useful results
• Thrive in collaborative environments
• Care deeply about AI safety and want your work to have real-world impact on how humanity navigates advanced AI
• Are comfortable working on sensitive projects that require discretion and integrity
• Have proven ability to lead cross-functional security initiatives and navigate complex organizational dynamics

Strong Candidates May Also Have

• Experience with offensive security research, vulnerability research, or exploit development
• Research or professional experience applying LLMs to security problems
• Track record in competitive CTFs, bug bounties, or other security-related competitions
• Experience building security tools or automation
• Track record of building demos or prototypes that communicate complex technical ideas
• Experience working with external stakeholders (policymakers, government, researchers)
• Familiarity with AI safety research and threat modeling for advanced AI systems

Logistics

Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact , advancing our long-term goals of steerable, trustworthy AI , rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions and workshops.

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As a Research Engineer on Alignment Science, you'll collaborate with other teams including Interpretability, Fine-Tuning, and the Frontier Red Team. Your responsibilities will include testing the robustness of our safety techniques, running multi-agent reinforcement learning experiments, building tooling to efficiently evaluate the effectiveness of novel LLM-generated jailbreaks, and contributing ideas, figures, and writing to research papers, blog posts, and talks.

You may be a good fit if you have significant software, ML, or research engineering experience, have some experience contributing to empirical AI research projects, and have some familiarity with technical AI safety research. Strong candidates may also have experience authoring research papers in machine learning, NLP, or AI safety, have experience with LLMs, have experience with reinforcement learning, and have experience with Kubernetes clusters and complex shared codebases.

The annual compensation range for this role is $350,000-$500,000 USD.

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Join us as Staff Software Engineer for Twilio Stytch's Agent team and help build the future of agent identity. You will be a foundational member of a team pioneering the next generation of authentication, verification, and identity solutions that will empower AI developers and protect users globally.

In this role, you'll:

• Build and own product capabilities for Stytch's agentic identity platform on Twilio.
• Design, implement, and maintain scalable, reliable distributed services, optimizing for security, latency, and developer experience.
• Partner with Product and Engineering leadership to set direction, translate customer needs into technical plans, and deliver high-impact roadmap features.
• Collaborate across Twilio and Stytch teams to align on architecture, integrate platform capabilities, and unblock cross-team initiatives.
• Write clean, maintainable, and well-tested code, setting a high bar for technical excellence across the team.
• Own the end-to-end lifecycle of new services, from initial design and prototyping through to production deployment and operational readiness.
• Mentor other engineers on the team, fostering a culture of innovation, ownership, and continuous learning.
• Communicate complex technical concepts effectively to diverse audiences, from fellow engineers to executive leadership.
• Stay at the forefront of industry trends and emerging threats in identity and authentication to ensure our products are secure and innovative.

We're seeking a talented Staff Engineer who brings deep hands-on technical expertise, a strategic mindset, and a passion for building secure, developer-first experiences.

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You'll train our base models through the complete post-training stack to deliver the production Claude models that users interact with.

Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

We conduct all interviews in Python, and this role may require responding to incidents on short-notice, including on weekends.

Responsibilities:

Implement and optimize post-training techniques at scale on frontier models

Conduct research to develop and optimize post-training recipes that directly improve production model quality

Design, build, and run robust, efficient pipelines for model fine-tuning and evaluation

Develop tools to measure and improve model performance across various dimensions

Collaborate with research teams to translate emerging techniques into production-ready implementations

Debug complex issues in training pipelines and model behavior

Help establish best practices for reliable, reproducible model post-training

You may be a good fit if you:

Thrive in controlled chaos and are energized, rather than overwhelmed, when juggling multiple urgent priorities

Adapt quickly to changing priorities

Maintain clarity when debugging complex, time-sensitive issues

Have strong software engineering skills with experience building complex ML systems

Are comfortable working with large-scale distributed systems and high-performance computing

Have experience with training, fine-tuning, or evaluating large language models

Can balance research exploration with engineering rigor and operational reliability

Are adept at analyzing and debugging model training processes

Enjoy collaborating across research and engineering disciplines

Can navigate ambiguity and make progress in fast-moving research environments

Strong candidates may also:

Have experience with LLMs

Have a keen interest in AI safety and responsible deployment

We welcome candidates at various experience levels, with a preference for senior engineers who have hands-on experience with frontier AI systems.

However, proficiency in Python, deep learning frameworks, and distributed computing is required for this role.

The annual compensation range for this role is $350,000-$500,000 USD.

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We're looking for prompt and context engineers to join our product engineering team to help build AI-first products, features, and evaluations. Your mission will be to bridge the gap between model capabilities and real product experience, working with product teams to build consistent, safe, and beneficial user experiences across all product surfaces.

Key Responsibilities

• Design, test, and optimize system prompts and feature-specific prompts that shape Claude's behavior across consumer and API products.
• Build and maintain comprehensive evaluation suites that ensure model quality and consistency across product launches and updates.
• Partner closely with product teams, research teams, and safeguards to ensure new features meet quality and safety standards.
• Play a critical role in model releases, ensuring smooth rollouts and catching regressions before they impact users.
• Help build and improve the frameworks and tools that allow teams to develop and test prompts and features with confidence.
• Mentor product engineers on prompt engineering best practices and help teams build their first evaluations.
• Work in a fast-paced environment where model capabilities advance daily, requiring quick adaptation and creative problem-solving.

What We're Looking For

• 5+ years of software engineering experience with Python or similar languages.
• Demonstrated experience with LLMs and prompt engineering (through work, research, or significant personal projects).
• Strong understanding of evaluation methodologies and metrics for AI systems.
• Excellent written and verbal communication skills – you'll need to explain complex model behaviors to diverse stakeholders.
• Ability to manage multiple concurrent projects and prioritize effectively.
• Experience with version control, CI/CD, and modern software development practices.

You Might Thrive in This Role If You…

• Get excited about the nuances of how language models behave and love finding creative ways to improve their outputs.
• Enjoy being at the intersection of research and product, translating cutting-edge capabilities into user value.
• Are comfortable with ambiguity and can define success metrics for novel AI features.
• Have a strong sense of ownership and drive projects from conception to production.
• Are passionate about building AI systems that are helpful, harmless, and honest.
• Thrive in collaborative environments and enjoy teaching others.

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The Impact You Will Have:

• Build: You will design and develop robust frontend interfaces and API backends (e.g., FastAPI routing user queries to model-serving endpoints). You will build solutions ranging from data-rich dashboards to enterprise chat solutions powered by the Mosaic AI Agent Framework.

• Architect: You will design secure and scalable application architectures that can suffice GTM requirements on building custom SaaS applications.

• Scale: You will create scalable applications that seamlessly connect to Databricks SQL via the Statement Execution API or Databricks SDK. You will establish CI/CD pipelines using Declarative Automation Bundles (DABs) to automate deployment across development, staging, and production workspaces.

What we look for:

• You have 5+ years of experience working as a Software Engineer, Data App Developer, or Full-Stack Engineer building interactive web applications.

• You are proficient in Python, DBSQL and/or Node.js. Experience with frameworks like Streamlit, Dash, Flask, FastAPI, React, or Express is required.

• You know the Databricks ecosystem. Familiarity with Unity Catalog, Databricks SQL, Databricks SDK for Python, and Model Serving is highly preferred.

• You have built for scale and security. Experience with CI/CD tools, Infrastructure as Code (specifically Databricks Asset Bundles), and implementing secure OAuth flows.

• You are passionate about applying AI. Experience integrating LLMs or Mosaic AI Agent Frameworks into application backends to deliver intelligent chat and RAG solutions.

• You excel in a collaborative environment. You can translate stakeholder requirements into intuitive user interfaces, working through dependencies and troubleshooting deployment errors or telemetry logs.

Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.

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Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole.

About the role

Anthropic's production models undergo sophisticated post-training processes to enhance their capabilities, alignment, and safety. As a Research Engineer on our Post-Training team, you'll train our base models through the complete post-training stack to deliver the production Claude models that users interact with.

You'll work at the intersection of cutting-edge research and production engineering, implementing, scaling, and improving post-training techniques like Constitutional AI, RLHF, and other alignment methodologies. Your work will directly impact the quality, safety, and capabilities of our production models.

Responsibilities

• Implement and optimize post-training techniques at scale on frontier models
• Conduct research to develop and optimize post-training recipes that directly improve production model quality
• Design, build, and run robust, efficient pipelines for model fine-tuning and evaluation
• Develop tools to measure and improve model performance across various dimensions
• Collaborate with research teams to translate emerging techniques into production-ready implementations
• Debug complex issues in training pipelines and model behavior
• Help establish best practices for reliable, reproducible model post-training

You may be a good fit if you:

• Thrive in controlled chaos and are energised, rather than overwhelmed, when juggling multiple urgent priorities
• Adapt quickly to changing priorities
• Maintain clarity when debugging complex, time-sensitive issues
• Have strong software engineering skills with experience building complex ML systems
• Are comfortable working with large-scale distributed systems and high-performance computing
• Have experience with training, fine-tuning, or evaluating large language models
• Can balance research exploration with engineering rigor and operational reliability
• Are adept at analyzing and debugging model training processes
• Enjoy collaborating across research and engineering disciplines
• Can navigate ambiguity and make progress in fast-moving research environments

Strong candidates may also:

• Have experience with LLMs
• Have a keen interest in AI safety and responsible deployment

Logistics

• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
• Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
• Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links,visit anthropic.com/careers directly for confirmed position openings.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact , advancing our long-term goals of steerable, trustworthy AI , rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.

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Our team focuses primarily but not exclusively on speech, building advanced steerable systems spanning end-to-end conversational systems, speech and audio understanding models, and speech synthesis capabilities. The team works closely with many collaborators across pretraining, finetuning, reinforcement learning, production inference, and product to get advanced audio technologies from early research to high-impact real-world deployments.

Responsibilities:

• Develop and train audio models, including conversational speech-to-speech, speech translation, speech recognition, text-to-speech, diarization, codecs, and generative audio models
• Work across abstraction levels, from signal processing fundamentals to large-scale model training and inference optimization
• Collaborate with teams across the company to develop and deploy audio technologies
• Communicate clearly and effectively with colleagues and stakeholders

Strong candidates may also have experience with:

• Large language model pretraining and finetuning
• Training diffusion models for image and audio generation
• Reinforcement learning for large language models and diffusion models
• End-to-end system optimization, from performance benchmarking to kernel optimization
• GPUs, Kubernetes, PyTorch, or distributed training infrastructure

Representative projects:

• Training state-of-the-art neural audio codecs for 48 kHz stereo audio
• Developing novel algorithms for diffusion pretraining and reinforcement learning
• Scaling audio datasets to millions of hours of high-quality audio
• Creating robust evaluation methodologies for hard-to-measure qualities such as naturalness or expressiveness
• Studying training dynamics of mixed audio-text language models
• Optimizing latency and inference throughput for deployed streaming audio systems

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As a Managing Director, SEO, you will be responsible for managing the P&L and growing revenue across the NAMER SEO practice. You will align the organization around a single vision for delivering AI SEO visibility and organic traffic. You will also senior sponsor our largest SEO client relationships, working with Brainlabs SEO teams to develop strategy and communicating SEO strategy to client-side C-level stakeholders.

Key responsibilities include:

• Managing the P&L and growing revenue across the NAMER SEO practice
• Aligning the organization around a single vision for delivering AI SEO visibility and organic traffic
• Senior sponsoring our largest SEO client relationships, working with Brainlabs SEO teams to develop strategy and communicating SEO strategy to client-side C-level stakeholders
• Co-leading GTM for AI Visibility efforts with the Chief Product Officer, leading new business SEO opportunities
• Defining the partners and tech to best serve Brainlabs' clients
• Guiding measurement strategy for SEO and AI Visibility
• Delivering SEO thought leadership across social media, Brainlabs' blog and industry speaking engagements

The ideal candidate will have 12+ years of SEO experience, including leading SEO teams, developing and executing SEO strategy for enterprise clients, and participating in sales processes. They will have an opinion on how AI and LLMs have changed SEO and how brands need to adapt to drive increased AI visibility. They will be held in high regard by media partners and colleagues, comfortable in a QBR, on stage or in a pitch closing media business, and have a track record of hiring, developing and growing successful teams.

We are looking for someone who lives our culture code every day, can take a pragmatic, first-principles approach, balance quick wins versus long-term tactics, and grow our SEO Practice revenue via both new business and new buying assignments from existing clients.

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The ideal candidate will have a strong background in computer science, robotics, machine learning, or a related field, and experience integrating agents into classical systems. They will also have a proven track record of novel application and experience including first-author publications, participation in peer-reviewed conferences, contribution to open-source projects, and demonstrated contribution to the ML and AI community.

In addition to your technical expertise, you will be a strong communicator and collaborator, able to work effectively with cross-functional teams to drive results. You will also be comfortable working in a fast-paced environment and adapting to changing priorities.

If you are a motivated and experienced engineer looking to join a dynamic team and contribute to cutting-edge technology, we encourage you to apply.

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Join the team as Twilio's next Software Engineer L3. This position is that of a Senior Software Engineer to join Twilio's Messaging Compliance Onboarding team. Programmable Messaging is Twilio's biggest product. To keep pace with the evolving messaging compliance ecosystem, we need strong engineers that can create innovative solutions to ensure compliance with Twilio partners.

In this role, you'll build and maintain multiple compliance program workflows, carrier/ecosystem integrations and customer interactions in the Compliance domain. You will design and develop elegant and scalable solutions across a wide variety of compliance program types including frontend UI experiences and backend APIs, that are highly available and responsive.

You will work through ambiguity, deliver quickly and with a high quality. Build towards achieving the next generation of architecture vision that empowers expansion of Compliance programs. Interact cross functionally across engineering teams within Twilio to align and build the product and architecture vision.

Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio.

We are always looking for people who will bring something new to the table!

*Required:

• 5+ years of experience and a strong fundamental knowledge of software development using JVM languages.

• Experience building web services incorporating best practices for external systems integration, including defensive and hardened approaches to mitigate downstream issues.

• Experience working with highly scalable APIs, high volume data pipelines and large distributed systems.

• Maintaining and operating cloud services.

• An unwillingness to settle for 'good enough', instead staying focused on longevity through well-tested code and continuous improvement.

• Demonstrated commitment to seeking diverse viewpoints and acting with intention to create an inclusive team environment.

• Excellent written and verbal communication skills. Ability to write down and present designs and decisions throughout the development lifecycle, collaborating with engineering and non-engineering roles.

Desired:

• 5+ years of Engineering experience, developing and maintaining high traffic services.

• Familiarity with DynamoDB, SQS, and data integration services like AWS glue

• Familiarity with LLMs, prompt optimizations to improve model accuracy, setting up evaluation pipelines

• Familiarity with Kubernetes, Temporal or similar workflow orchestration

• Experience working with frontend libraries like React or similar.

Compensation:

*Please note this role is open to candidates outside of California, Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, New Jersey, New York, Vermont, Washington D.C., and Washington State.

The estimated pay ranges for this role are as follows:

• Based in Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, Vermont or Washington D.C.: $138,700 - $173,400

• Based in New York, New Jersey, Washington State, or California (outside of the San Francisco Bay area): $146,800 - $183,600

• Based in the San Francisco Bay area, California: $163,100 - $203,900.

This role may be eligible to participate in Twilio's equity plan and corporate bonus plan. All roles are generally eligible for the following benefits: health care insurance, 401(k) retirement account, paid sick time, paid personal time off, paid parental leave.

Applications for this role are intended to be accepted until 4/10/2026, but may change based on business needs.

Twilio thinks big. Do you? We like to solve problems, take initiative, pitch in when needed, and are always up for trying new things. That's why we seek out colleagues who embody our values , something we call Twilio Magic. Additionally, we empower employees to build positive change in their communities by supporting their volunteering and donation efforts. So, if you're ready to unleash your full potential, do your best work, and be the best version of yourself, apply now!

If this role isn't what you're looking for, please consider other open positions.

Twilio is proud to be an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Additionally, Twilio participates in the E-Verify program in certain locations, as required by law.

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