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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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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You will build reliable, scalable data products and user experiences that power AI/ML modeling, agentic workflows, and reporting,working end-to-end from data ingestion and transformation through to UI. Our Python-based data platform is undergoing a major evolution toward a modern, cloud-native ELT architecture. We are standardizing on Snowflake as our central data platform and dbt as our core transformation framework, implementing scalable, maintainable ELT practices that simplify ingestion, modeling, and deployment.

This role will be pivotal in independently designing and building robust data pipelines and semantic layers that directly power our AI and machine learning initiatives,delivering clean, reliable, and well-modeled data assets to our data science team for feature engineering, model training, and production inference. You will collaborate closely (primarily via remote channels) with data scientists and ML engineers to ensure our data ecosystem is optimized for experimentation speed, model performance, and seamless integration into downstream products and services.

Key Responsibilities

• Remote collaboration & communication: Operate effectively as an offshore member of a distributed team, proactively communicating status, risks, and blockers across time zones and coordinating overlap with US working hours as needed.

• Full-stack data engineering: Build across the entire stack, including data ingestion/acquisition and transformation, APIs, front-end components, and automated test suites, delivering production-grade solutions with minimal hand-holding.

• Autonomous delivery & ownership: Take end-to-end ownership of features and projects,clarifying requirements, breaking work into milestones, estimating timelines, and delivering high-quality, well-documented solutions.

• Specification and design: Translate short- and long-term business requirements, architectural considerations, and competing timelines into clear, actionable technical specifications and design documents.

• Code quality: Write clean, maintainable, efficient code that adheres to evolving standards and quality processes, including unit tests and isolated integration tests in containerized environments.

• Continuous improvement: Contribute to agile practices and provide input on technical strategy, architectural decisions, and process improvements, continuously suggesting better tools, patterns, and automation.

Required Skills & Experience

• Professional experience: 5+ years in software engineering, with a full-stack background building complex, scalable data-engineering pipelines using data warehouse technology, SQL with dbt, Python, AWS with Terraform, and modern UI technologies.

• Modern data engineering: Strong experience with medallion data architecture patterns using data warehouse technologies (e.g., Snowflake), data transformation tooling (e.g., dbt), BI tooling, and NoSQL data marts (e.g., Elasticsearch/OpenSearch).

• Testing and QA: Solid understanding of unit testing, CI/CD automation, and quality assurance processes for both data pipeline testing and operational data quality tests.

• Remote work & autonomy: Proven track record working in a remote or distributed environment, demonstrating self-motivation, reliable execution, and the ability to make sound technical decisions independently.

• Agile methodology: Working knowledge of Agile development practices and workflows (e.g., sprint planning, stand-ups, retrospectives) in a distributed team setting.

• Education: Bachelor’s or Master’s degree in Computer Science, Statistics, Informatics, Information Systems, or a related quantitative field.

Preferred Skills & Experience

• Machine learning and AI: Hands-on experience with large language models (LLMs) and agentic frameworks/workflows.

• Search and analytics: Familiarity with the ELK stack (Elasticsearch, Logstash, Kibana) for search and analytics solutions.

• Cloud expertise: Experience with AWS cloud services; familiarity with SageMaker; and CI/CD tooling such as GitHub Actions or Jenkins.

• Front-end expertise: Experience building user interfaces with Angular or a modern UI stack.

• Financial domain knowledge: Broad understanding of equities, fixed income, derivatives, futures, FX, and other financial instruments.

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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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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 role owns large, ambiguous problem spaces directly tied to company metrics and translates them into a clear six-month technical roadmap, leading delivery for 15–20 engineers across team boundaries. You will collaborate on ideas that shape area-level decisions, communicate effectively at all levels, and continuously integrate evolving business context into product and platform direction.

You will set and model high standards for engineering and operational excellence,driving reliability, scalability, execution rigor, and long-term maintainability across foundational systems,while remaining deeply hands-on through daily coding, design authorship, critical reviews, and architectural leadership.

The role influences Core Engineering roadmaps, establishes technical direction, and brings strong instincts for high-quality consumer-facing experiences. You will mentor senior talent, raising the technical bar through coaching and example, and extend your impact through org-level technical leadership.

Over time, this leader grows from a cross-team technical driver into an org-level technical strategist, optimizing for the company as a whole rather than a single scope.

This team will own project Optimize Activation and Engagement Flows for Team Users. Lead a multi-year plan to modernize onboarding and activation, clean up core Dropbox surfaces, and build intelligent, adaptive systems that boost team activation, invites, and long-term engagement across platforms.

Opportunity for large impact on the business helping Teams users activate on the right features to drive down churn.

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You will set and model high standards for engineering and operational excellence, driving reliability, scalability, execution rigor, and long-term maintainability across foundational systems. You will remain deeply hands-on through daily coding, design authorship, critical reviews, and architectural leadership. You will influence Core Engineering roadmaps, establish technical direction, and bring strong instincts for high-quality consumer-facing experiences.

You will mentor senior talent, raising the technical bar through coaching and example, and extend your impact through org-level technical leadership. Over time, you will grow from a cross-team technical driver into an org-level technical strategist, optimizing for the company as a whole rather than a single scope.

This team will own project Optimize Activation and Engagement Flows for Team Users. You will lead a multi-year plan to modernize onboarding and activation, clean up core Dropbox surfaces, and build intelligent, adaptive systems that boost team activation, invites, and long-term engagement across platforms. Opportunity for large impact on the business helping Teams users activate on the right features to drive down churn.

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Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime.

At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work.

Creating a career you love? It’s Possible.

At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that.

To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.

Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think.

You can read more about our AI interview philosophy and how we use AI in our recruiting process here.

We're building a new capability at Pinterest: embedding AI-native engineering directly inside our business functions. The AI Solutions Engineer will partner with teams across Marketing, Finance, Sales, HR, Legal, and other functions to surface high-value automation opportunities, then design and ship the AI-powered tools that bring those opportunities to life.

This is a hands-on, mid-level software engineering role for someone who is equally comfortable reading a business process flowchart and writing production-grade Python.

You'll work end-to-end , from discovery and scoping through prototyping, launch, and iteration , using the latest agentic frameworks, tool-calling patterns, and responsible AI practices.

What you'll do:

• Discover and scope AI opportunities: Partner with internal teams across corporate functions to understand their workflows, pain points, and goals, and identify high‑value AI/automation opportunities.
• Map and improve business processes: document current workflows, identify bottlenecks, and propose AI‑enabled changes that deliver clear business outcomes (e.g., time or cost savings, improved quality or compliance).
• Design end-to-end AI solutions: Design and implement AI‑enabled tools and workflows that integrate with existing systems and data sources, and that are intuitive for non‑technical users.
• Build and ship production-quality software: Write clean, maintainable code and tests.
• Pilot, rollout, and drive adoption: Pilot, roll out, and drive adoption of solutions by working closely with end‑users, gathering feedback, and iterating based on real‑world usage.
• Champion for responsible AI: Ensure solutions follow privacy, security, and compliance expectations, especially when working with sensitive or regulated data.
• Build for reuse: Create and share reusable patterns, components, and documentation to make future AI/automation work faster and more consistent across teams.
• Accelerate Workflows with Generative AI and Automation: Leverage AI to accelerate execution (e.g., draft, prototype, outline), explore alternative solutions using AI (iterate, compare approaches), synthesize information with AI (summarize, distill key themes), automate repeatable work (documentation, reporting, QA checks)

What we're looking for:

We're looking for mid-level engineers who have already shipped something real with AI , and who can work as a peer with non-technical business partners, not just as an order-taker.

Specifically, you bring:

• Software engineering foundation. A CS, Engineering, Data Science, or related degree (or equivalent experience), with demonstrated ability to build and operate production systems , backend services, internal tools, integrations, or data applications.
• Hands-on AI and automation delivery. You've shipped AI-powered or automation-driven solutions in a real environment.
• Agentic AI literacy. You understand how modern agentic systems are constructed , the difference between local and remote agents, how MCP (Model Context Protocol) works, what Agent Skills and Hooks are for, and how A2A (Agent-to-Agent) coordination is structured.
• System design and architecture thinking. You can sketch a data flow, reason about integration points, evaluate trade-offs between approaches, and design for failure , including fallbacks, retry logic, timeouts, and human escalation paths.
• Data and security judgment. You understand data access controls, the risks of giving AI broad access to sensitive information, PII minimization, audit logging, and what responsible data handling looks like in an enterprise environment.
• Business function acumen. You can engage credibly with stakeholders in Marketing, Finance, Sales, HR, Legal, or Operations , understanding their workflows, KPIs, and constraints well enough to scope solutions that fit their real needs.
• Clear, collaborative communication. You can explain architecture trade-offs to a Finance Manager and debug a prompt failure with an engineer in the same afternoon.

Preferred Qualifications:

• Experience working embedded with or alongside corporate / G&A functions (Finance, Legal, HR, Marketing, Sales Operations, or similar).
• Practical experience with agentic frameworks such as LangGraph, Claude Agent SDK, or comparable tooling.
• Familiarity with MCP server design , including building, deploying, and securing MCP-compliant tool servers.
• Experience designing and evaluating AI outputs at scale: eval sets, sampling pipelines, human-in-the-loop review queues, or A/B testing of AI-powered features.
• Exposure to responsible AI frameworks: data minimization, differential privacy concepts, model output auditing, or working in PII-sensitive / regulated domains.
• Experience with RAG (Retrieval-Augmented Generation) pipelines, vector databases, or enterprise search integrations.
• Familiarity with CI/CD for AI: prompt versioning, model version pinning, regression testing for LLM-powered features.

Relocation Statement:

This position is not eligible for relocation assistance.

Visit our PinFlex page to learn more about our working model.

In-Office Requirement Statement:

This role will need to be in the office for in-person collaboration 1-2 times every 6-months and therefore can be situated anywhere in the country.

#LI-REMOTE #LI-KBF

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Your responsibilities will include:

• Technical Delivery and Implementation: Own the end-to-end technical delivery of AI solutions, including writing code, configuring systems, and resolving issues, while reviewing the work of junior team members to ensure quality deployment and measurable business impact.

• AI Solution Development: Take ownership of designing and implementing scalable production systems, including AI and Large Language Model (LLM) based intelligent agents and automated workflows built on the Salesforce platform.

• Custom Agentic AI Engineering: Work directly with stakeholders to design and build custom intelligent agents using the Elastic Agent Builder platform, ensuring solutions meet unique business requirements and integrate smoothly with existing tool ecosystems.

• Data Configuration and Integration: Own the full data lifecycle, from data model design to building efficient processing pipelines and establishing integration strategies. Ensure data is optimized and secure for AI applications, including in complex enterprise environments.

• Technical Problem Solving: Identify, analyze, and resolve technical challenges across all phases of solution delivery, from data integration to model deployment and agent orchestration. Serve as a reliable resource for unblocking progress.

• Agentic Innovation: Develop expertise in the Elastic platform, pushing its capabilities forward. Lead the development of custom intelligent agents, automate business processes, and shape user experiences. Insights from the field will directly influence product enhancements and platform direction.

• Client Partnership: Embed with client teams to understand their operational challenges and goals. Translate requirements into clear technical designs, build strong relationships, and serve as a trusted technical advisor.

• Debugging and Root Cause Analysis: Perform thorough analysis, debugging, and root cause identification for complex system interactions, data flows, and AI model behaviors to optimize performance and prevent recurring issues.

• Prototyping and Iteration: Rapidly develop proofs-of-concept and minimum viable products, often coding alongside client teams to demonstrate capabilities and gather feedback for iterative refinement.

• Engineering Best Practices: Apply and promote standards for code quality, scalability, security, and maintainability across all deployed solutions.

Requirements include:

• At least 5 years' experience in a hands-on, end-to-end delivery role for scalable production solutions in a professional environment

• Expert-level proficiency in one or more programming languages (e.g., JavaScript, Java, Python)

• Extensive experience building and deploying solutions with AI/LLM technologies, including integrating LLMs, applying AI orchestration frameworks (e.g., LangChain, LlamaIndex), prompt engineering techniques, and agentic frameworks

• Deep expertise in data modeling, processing, integration, and analytics, with proficiency in enterprise data platforms (e.g., Salesforce Data Cloud, Snowflake, Databricks, BigQuery)

• Strong collaboration, communication, and presentation skills, both written and verbal, with the ability to explain complex technical concepts to technical and non-technical partners

• Track record of leading technical engagements, mentoring junior team members, and taking responsibility for technical aspects of projects

This role is eligible to participate in Elastic's stock program and has a competitive salary range of $94,300-$149,200 USD, with an alternate range of $113,300-$179,200 USD in select locations.

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Your 下 responsibilities will include:

• Owning the agentic tools platform, including the registry of capabilities agents can invoke, the standards for how tools are built, and the governance for how they're deployed.
• Balancing the tension between enabling rapid tool development and maintaining the reliability that production agents demand.
• Architecting integration strategy, including determining which integrations unlock disproportionate value, negotiating technical partnerships, and defining the abstraction layers that make integrations composable rather than brittle.
• Driving agentic execution excellence, including partnering with ML engineers on tool selection optimization, prompt engineering for reliable tool invocation, and error handling patterns that make agents resilient.
• Enabling internal tool development, including building the developer experience,documentation, templates, testing frameworks, deployment pipelines,that lets teams ship new tools without deep platform expertise.

In this role, you will be working at the forefront of agentic technology, evaluating innovations and determining which advances warrant immediate adoption versus patient observation. You will also be responsible for navigating the agentic frontier, including bringing external best practices to ZoomInfo while contributing learnings back to the community.

To be successful in this role, you will need to have a strong background in product management, with 6-15 years of experience in AI/ML infrastructure, developer platforms, or integration products. You should also have direct experience with production agentic systems, hands-on familiarity with agentic frameworks, and a track record of building platform products where engineering teams are your customers.

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You will lead product vision and champion the developer experience, designing intuitive, scalable workflows that balance ease-of-access with research-grade quality. You will also scale the ecosystem by launching strategic features, integrations, and partnerships that meet developers where they are, expanding Kaggle's reach and influence across the global AI community.

In addition, you will productize the frontier by identifying emergent AI evaluation trends and novel paradigms, translating them into scalable platform features that act as a 'north star' for the industry. You will drive internal and external impact by partnering cross-functionally with Google teams and external frontier labs to ensure Kaggle's aggregate signals directly inform and accelerate foundation model development.

You will also build sustainable systems and business models by addressing complex platform scaling challenges, such as implementing flexible compute options to support compute-heavy agentic evaluation workloads.

To be successful in this role, you will need 7+ years of product management experience, with a proven track record of successfully shipping and scaling complex, highly technical software products. You will also need deep domain expertise in the modern AI ecosystem, with a hands-on, opinionated understanding of LLMs, agentic frameworks, and current methodologies for model benchmarking and evaluation.

You will be comfortable with ambiguity and able to define product direction in a fast-moving, novel space. You will also have a strong existing network or previous experience working directly with top-tier AI labs, research organizations, or open-source AI communities.

The US base salary range for this full-time position is between $192,000 USD - $278,000 USD + bonus + equity + benefits.

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What you'll do

• Architect multi-agent systems and agentic workflows for IP R&D automation
• Design and implement AI copilots with tool use, planning, and memory capabilities

What you need

• 5+ years in software development with AI/ML focus
• Expertise in GenAI, RAG, and agentic AI systems

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