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.

Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company.

About the team

The Data Intelligence & Analytics organization builds the core data platform and internal products that power decision-making across the company. We design and operate large-scale data systems, own the company’s data lake, ingestion infrastructure, and platform tooling, and develop end-to-end applications that transform complex datasets into fast, reliable, business-critical products used daily by go-to-market, product, and engineering teams.

Our work sits at the intersection of data platforms, distributed systems, and product development, giving engineers the opportunity to own meaningful problems across the stack and build systems that truly run the business.

About the role

We are looking for an experienced Machine Learning Engineer to join our Bengaluru team and help scale the next generation of our AI/ML models. In this role, you will build and operate the pipelines behind AI-driven applications, Agents, Chatbots that power teams across the company, including go-to-market, engineering, and product.

Because the products we build are initiated and owned by the team, you will be involved end-to-end , from shaping requirements and designing systems to implementation, deployment, and long-term ownership. You will focus on building scalable, reliable services and application backends, partnering closely with data and full-stack engineers to deliver new features and operate the pipelines and platforms behind our products.

Our stack spans multiple languages and technologies, including Python, React, and TypeScript, and continues to evolve. Many of our applications also incorporate strong AI components, giving you opportunities to work with modern AI infrastructure and tools such as vector databases, MCP-based services, and Workers AI.

What you'll do

Deploy, manage & support ML Applications & Services on Kubernetes

Understand MLOps landscape i.e tooling, tech stack, source systems etc. and work on introducing new tools and solutions for ML & AI initiatives.

Partner and align with Data Scientists, Data Engineers and internal teams to deliver ML solutions in a globally distributed environment.

Lead development of efficiencies to boost model training to deployment lead times

Understand business/product strategy and high-level roadmap and align analysis efforts to enable them with data insights and help achieve their strategic goals.

Leverage Cloudflare products and services for AI & ML initiatives and applications

Use software engineering best practices to publish model scores/insights/learnings at scale within the company.

Examples of desirable skills, knowledge and experience

M.S or Ph.D in Computer Science, Statistics, Mathematics, or other quantitative fields.

5+ years of ML Engineering experience with proven industry experience in a large scale environment (PBs scale & globally distributed teams).

Strong experience in scientific computing using Python with Scikit-Learn & PyTorch or Tensorflow.

Strong experience working with Docker & Kubernetes to build and deploy applications and systems.

Experience working with ML Platform tools (AirFlow, Argo Workflows, ArgoCD) preferred.

Experience working with Data Scientists to deploy Machine Learning applications systems for training, inference and observability.

Experience with Full-stack Web technologies and languages (FastAPI, Streamlit, JavaScript/TypeScript, Cloudflare Workers, etc.) preferred with the ability to quickly learn and contribute across a multi-language stack.

Experience with Terraform, Google Cloud Platform (or any other public cloud equivalent) etc.

Experience working with CI/CD systems, version control (Git, Bitbucket, etc.), testing (Pytest, etc.) and DevOps tools.

Experience with Databases such as BigQuery, Postgres, SQLite and ETL/ELT practices

Strong cross-functional collaboration experience with data engineering and data analysts teams within the function.

Proficiency in large language models and the frameworks like Langchain, LangGraph, etc. necessary for implementing GenAI applications, such as chatbots and related use cases.

Strong communication and presentation skills catered to different audiences within the company.

Demonstrated ability to design scalable, reliable, and observable systems, with experience influencing architecture and improving platform foundations.

Strong problem-solving and communication skills, with a track record of working effectively with cross-functional partners and driving projects through ambiguous problem spaces.

Experience mentoring engineers, leading by example in code and design, and contributing to a culture of technical excellence.

Fraud Alert: Do not fall victim to recruitment fraud. Cloudflare never charges application fees or requires candidates to purchase third-party certifications or training as a condition of employment. All official communication comes strictly from @cloudflare.com email addresses.

What Makes Cloudflare Special?

We’re not just a highly ambitious, large-scale technology company. We’re a highly ambitious, large-scale technology company with a soul. Fundamental to our mission to help build a better Internet is protecting the free and open Internet.

Project Galileo: Since 2014, we've equipped more than 2,400 journalism and civil society organizations in 111 countries with powerful tools to defend themselves against attacks that would otherwise censor their work, technology already used by Cloudflare’s enterprise customers--at no cost.

Athenian Project: In 2017, we created the Athenian Project to ensure that state and local governments have the highest level of protection and reliability for free, so that their constituents have access to election information and voter registration. Since the project, we've provided services to more than 425 local government election websites in 33 states.

1.1.1.1: We released 1.1.1.1 to help fix the foundation of the Internet by building a faster, more secure and privacy-centric public DNS resolver. This is available publicly for everyone to use - it is the first consumer-focused service Cloudflare has ever released.

Here’s the deal - we don’t store client IP addresses never, ever. We will continue to abide by our privacy commitment and ensure that no user data is sold to advertisers or

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Our dedication to remote-first work, and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day.

As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding.

Join the team as our next Staff Software Engineer in the Enterprise AI Engineering team.

Twilio is undergoing a major business transformation powered by Enterprise AI, supported by a dedicated engineering team building the foundations for a unified, secure, and scalable operating system across GTM functions (Sales, Support, Operations, etc.) as well as Internal non-GTM functions (Finance, HR, Legal, etc.).

Our platform is designed to support a multitude of business functions by deploying intelligent agentic solutions that automate complex workflows and deliver unprecedented user experiences.

We're building the future of work at Twilio, and this role offers the opportunity to be at the forefront of enterprise AI innovation.

This role focuses specifically on transforming how Twilio's Customer Support organization operates through AI-powered tools and agentic products.

We are looking for Full-Stack Engineers who view AI as a fundamental shift in the software development lifecycle of engineering products and the delivery of beautiful, engaging user experiences.

This is an opportunity to deliver innovative software products and solutions across every business function in the company such as Sales, Marketing, GTM, HR, Finance and Legal.

Joining this team means building production grade, full-stack AI applications.

You won’t just be wrapping APIs; you will be engineering the entire lifecycle of agentic applications.

As a Staff Software Engineer within Enterprise AI, you are the technical heartbeat of our products.

Your role is to bridge the gap between bleeding-edge AI research and robust, full-stack production systems.

Responsibilities:

• Co-lead the design and development of our software infrastructure, driving technical vision and strategy to ensure scalability, reliability, and performance.

• Drive the development of sophisticated, stateful web applications.

• Serve as developer leader in distributed systems, data technologies, with strong software engineering skills.

• Drive technical innovation and research to stay at the forefront of emerging data technologies and best practices.

• Mentor and elevate a team of high-performing engineers.

• Collaborate closely with cross-functional teams to understand business requirements and translate them into scalable and efficient technical solutions.

• Continuously adapt to the evolving JavaScript ecosystem to maximize engineering efficiency.

• Ensure data quality, integrity, and security throughout the data lifecycle, adhering to industry best practices and compliance standards.

Qualifications:

• Bachelor's degree in Computer Science, Engineering, or a related field.

• 8+ years of experience in data engineering, software development, or a related field, with at least 3 years in a technical leadership role.

• Experience with full-stack development building web apps, using modern programming languages such as JavaScript, Typescript or React.

• Proven track record of architecting and delivering complex data projects at scale, with a deep understanding of data infrastructure and distributed systems.

• Strong understanding of data modeling, data warehousing, and ETL processes, with experience designing and optimizing data pipelines.

• Excellent communication and collaboration skills, with the ability to influence technical decisions and drive alignment across teams.

• Strong leadership skills, with a track record of mentoring and developing high-performing engineering teams.

• Demonstrated ability to thrive in a fast-paced, dynamic environment and deliver results under tight timelines.

Desired:

• Experience developing production-quality LLM applications and using modern agent frameworks such as Langchain, Langgraph, Llamaindex, LangSmith, LangFuse, CrewAI, and/or others is a plus.

• Expertise in big data technologies such as Hadoop, Spark, Kafka, and cloud-based data services (AWS/GCP/Azure).

Location:

This role will be remote, and based in Canada.

Travel:

We prioritize connection and opportunities to build relationships with our customers and each other.

For this role, you may be required to travel occasionally to participate in project or team in-person meetings.

What We Offer:

Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more.

Offerings vary by location.

Based on role, employees may also be eligible for additional compensation and benefits, including but not limited to incentive programs, commissions, equity grants, health and wellness benefits, retirement contributions, and paid time off.

The estimated pay ranges for this role are as follows:

• $160,320 - $200,400

• Target Bonus Percentage 15% (When Applicable)

The successful candidate’s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location.

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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Our work spans secure identity flows, defenses against emerging threats like prompt injection, and privacy-first systems that scale globally.

We’re seeking a Principal Software Engineer to contribute to the development of security features and solutions that harness agentic AI to protect customers and enable new capabilities in Copilot.

You’ll design, build, and ship AI-powered defenses, secure orchestration frameworks, and enabling technologies that empower Copilot to act safely and responsibly at scale.

This role requires solid engineering skills, creativity in applying agentic AI to security challenges, and a passion for building systems that balance innovation with trust.

Your work will directly shape how hundreds of millions of users experience safe, trustworthy, and innovative AI.

You’ll be at the forefront of defining how agentic AI can proactively defend users, mitigate emerging threats, and unlock new secure scenarios,making a global impact on Microsoft’s most transformative products.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more.

As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals.

Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50-mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week.

This expectation is subject to local law and may vary by jurisdiction.

Responsibilities:

Develop and ship agentic AI-powered security features that protect users from threats such as prompt injection, adversarial manipulation, and abuse of agentic workflows.

Design and implement secure orchestration frameworks that enable Copilot to safely delegate, coordinate, and execute actions across devices, services, and platforms.

Invent and apply new intelligent agents that leverage information flow analysis and apply common sense and judgement guardrails for security and privacy.

Collaborate with product, engineering, security, privacy, and AI teams to drive adoption of agentic security patterns and best practices across Copilot and MAI.

Monitor key metrics for agentic AI security and innovation, using data-driven insights to improve defenses and enablement.

Align with central Microsoft security and AI roadmaps, landing platform capabilities in Copilot and MAI consumer scenarios.

Document secure agentic AI patterns, ensuring they address novel risks, support safe delegation, and enable responsible orchestration of actions.

Qualifications:

Required Qualifications:

Bachelor’s Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, Go, or Python OR equivalent experience.

Preferred Qualifications:

Master’s Degree in Computer Science or related technical field AND 10+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor’s Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

8+ years in technical engineering roles building large-scale services.

8+ years hands-on experience designing and operating security-critical or AI-powered systems at scale, including agentic AI, secure orchestration, or advanced threat defenses.

Proven ability to design, build, and ship agentic AI features or frameworks.

Ability to clearly explain complex systems and security concepts to technical and non-technical stakeholders and influence cross-org roadmaps.

Experience building production agent systems using frameworks such as LangGraph, Amazon Strands SDK, or similar platforms; familiarity with agentic design patterns including tool calling, multi-agent coordination, and secure delegation patterns.

Hands-on experience with distributed training frameworks (Ray, Slurm, HPC), containerization and orchestration technologies (Docker, Kubernetes) for ML model deployment, and ML lifecycle management in production environments.

Experience designing evaluation frameworks for LLM-based applications and implementing observability for agent systems using tools such as Phoenix, MLFlow, LangFuse, or custom eval harnesses; understanding of AI safety evaluation methodologies including adversarial testing and red-teaming.

Experience integrating with Azure AI services, Azure OpenAI Service, or Microsoft security platforms (Azure AD, Defender, Purview).

Track record of mentoring engineers, driving adoption of secure agentic AI standards across product teams, and influencing technical roadmaps while balancing innovation velocity with fundamentals.

#MicrosoftAI Software Engineering IC6 – The typical base pay range for this role across the U.S. is USD $163,000 – $296,400 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $220,800 – $331,200 per year. Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay

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Our work spans secure identity flows, defenses against emerging threats like prompt injection, and privacy-first systems that scale globally.

We’re seeking a Principal Software Engineer to contribute to the development of security features and solutions that harness agentic AI to protect customers and enable new capabilities in Copilot.

You’ll design, build, and ship AI-powered defenses, secure orchestration frameworks, and enabling technologies that empower Copilot to act safely and responsibly at scale.

This role requires solid engineering skills, creativity in applying agentic AI to security challenges, and a passion for building systems that balance innovation with trust.

Your work will directly shape how hundreds of millions of users experience safe, trustworthy, and innovative AI.

You’ll be at the forefront of defining how agentic AI can proactively defend users, mitigate emerging threats, and unlock new secure scenarios,making a global impact on Microsoft’s most transformative products.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more.

As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals.

Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Responsibilities:

Develop and ship agentic AI-powered security features that protect users from threats such as prompt injection, adversarial manipulation, and abuse of agentic workflows.

Design and implement secure orchestration frameworks that enable Copilot to safely delegate, coordinate, and execute actions across devices, services, and platforms.

Invent and apply new intelligent agents that leverage information flow analysis and apply common sense and judgement guardrails for security and privacy.

Collaborate with product, engineering, security, privacy, and AI teams to drive adoption of agentic security patterns and best practices across Copilot and MAI.

Monitor key metrics for agentic AI security and innovation, using data-driven insights to improve defenses and enablement.

Align with central Microsoft security and AI roadmaps, landing platform capabilities in Copilot and MAI consumer scenarios.

Document secure agentic AI patterns, ensuring they address novel risks, support safe delegation, and enable responsible orchestration of actions.

Qualifications:

Bachelor’s Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, Go, or Python OR equivalent experience.

Master’s Degree in Computer Science or related technical field AND 10+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor’s Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

8+ years in technical engineering roles building large-scale services.

8+ years hands-on experience designing and operating security-critical or AI-powered systems at scale, including agentic AI, secure orchestration, or advanced threat defenses.

Proven ability to design, build, and ship agentic AI features or frameworks.

Ability to clearly explain complex systems and security concepts to technical and non-technical stakeholders and influence cross-org roadmaps.

Experience building production agent systems using frameworks such as LangGraph, Amazon Strands SDK, or similar platforms; familiarity with agentic design patterns including tool calling, multi-agent coordination, and secure delegation patterns.

Hands-on experience with distributed training frameworks (Ray, Slurm, HPC), containerization and orchestration technologies (Docker, Kubernetes) for ML model deployment, and ML lifecycle management in production environments.

Experience designing evaluation frameworks for LLM-based applications and implementing observability for agent systems using tools such as Phoenix, MLFlow, LangFuse, or custom eval harnesses; understanding of AI safety evaluation methodologies including adversarial testing and red-teaming.

Experience integrating with Azure AI services, Azure OpenAI Service, or Microsoft security platforms (Azure AD, Defender, Purview).

Track record of mentoring engineers, driving adoption of secure agentic AI standards across product teams, and influencing technical roadmaps while balancing innovation velocity with fundamentals.

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Our work spans secure identity flows, defenses against emerging threats like prompt injection, and privacy-first systems that scale globally.

We're seeking a Principal Software Engineer to contribute to the development of security features and solutions that harness agentic AI to protect customers and enable new capabilities in Copilot.

You'll design, build, and ship AI-powered defenses, secure orchestration frameworks, and enabling technologies that empower Copilot to act safely and responsibly at scale.

This role requires solid engineering skills, creativity in applying agentic AI to security challenges, and a passion for building systems that balance innovation with trust.

Your work will directly shape how hundreds of millions of users experience safe, trustworthy, and innovative AI.

As employees, we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals.

Each day, we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Responsibilities:

• Develop and ship agentic AI-powered security features that protect users from threats such as prompt injection, adversarial manipulation, and abuse of agentic workflows.

• Design and implement secure orchestration frameworks that enable Copilot to safely delegate, coordinate, and execute actions across devices, services, and platforms.

• Invent and apply new intelligent agents that leverage information flow analysis and apply common sense and judgement guardrails for security and privacy.

• Collaborate with product, engineering, security, privacy, and AI teams to drive adoption of agentic security patterns and best practices across Copilot and MAI.

• Monitor key metrics for agentic AI security and innovation, using data-driven insights to improve defenses and enablement.

• Align with central Microsoft security and AI roadmaps, landing platform capabilities in Copilot and MAI consumer scenarios.

• Document secure agentic AI patterns, ensuring they address novel risks, support safe delegation, and enable responsible orchestration of actions.

Qualifications:

• Bachelor's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, Go, or Python OR equivalent experience.

• 8+ years in technical engineering roles building large-scale services.

• 8+ years hands-on experience designing and operating security-critical or AI-powered systems at scale, including agentic AI, secure orchestration, or advanced threat defenses.

• Proven ability to design, build, and ship agentic AI features or frameworks.

• Ability to clearly explain complex systems and security concepts to technical and non-technical stakeholders and influence cross-org roadmaps.

• Experience building production agent systems using frameworks such as LangGraph, Amazon Strands SDK, or similar platforms; familiarity with agentic design patterns including tool calling, multi-agent coordination, and secure delegation patterns.

• Hands-on experience with distributed training frameworks (Ray, Slurm, HPC), containerization and orchestration technologies (Docker, Kubernetes) for ML model deployment, and ML lifecycle management in production environments.

• Experience designing evaluation frameworks for LLM-based applications and implementing observability for agent systems using tools such as Phoenix, MLFlow, LangFuse, or custom eval harnesses; understanding of AI safety evaluation methodologies including adversarial testing and red-teaming.

• Experience integrating with Azure AI services, Azure OpenAI Service, or Microsoft security platforms (Azure AD, Defender, Purview).

• Track record of mentoring engineers, driving adoption of secure agentic AI standards across product teams, and influencing technical roadmaps while balancing innovation velocity with fundamentals.

#MicrosoftAI

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We are seeking an experienced and innovative AI Product Engineer – Agentic Platforms to join our Financial Services Artificial Intelligence & Business Lines (FS-ABL) practice. This role is ideal for a consulting technologist with deep expertise in modern GenAI tooling, agentic system design, and enterprise SDLC, who can partner directly with clients to envision, design, develop, and deploy Agentic AI platforms in regulated environments.

In this role, you will work at the intersection of client advisory, AI product engineering, and delivery execution, helping banks, insurers, and capital markets firms transition from GenAI pilots to production-grade, governed, multi-agent systems. You will apply leading GenAI frameworks and LLM platforms , including Anthropic, OpenAI, LangChain, LangGraph, DSPy, and vector databases,while operating across the full Agentic SDLC.

P&C Insurance knowledge and experience is a significant plus. Additionally, familiarity with core insurance platforms like Guidewire, DuckCreek or Majesco will be extremely helpful to succeed in this role.

We are looking for candidates across all levels of experience and expertise - junior through senior level AI Product Engineers.

Responsibilities

Client Advisory & Product Vision

Partner directly with Financial Services clients to identify, prioritize, and shape Agentic AI use cases across customer operations, underwriting, claims, risk, compliance, finance, and technology.

Lead client workshops to define agent personas, responsibilities, autonomy boundaries, human-in-the-loop checkpoints, and escalation logic.

Translate evolving business needs into agentic product backlogs, roadmaps, and MVP definitions.

Support executive conversations around GenAI platform strategy, operating models, vendor selection, and scale-out approaches.

Agentic Platform & Architecture Design

Design and implement multi-agent architectures using modern GenAI tooling, including:

Planner, executor, reviewer/critic, and supervisor agents

Tool-calling and function-calling agents

Memory-enabled agents (conversation, semantic, episodic, and structured memory)

Leverage LangChain and LangGraph for agent orchestration, workflows, and control flow.

Apply DSPy and declarative prompt optimization techniques for repeatability, performance tuning, and regression control.

Design agent interaction patterns such as hierarchical agents, collaborating agents, and event-driven agent workflows.

Define standardized agent contracts, interfaces, and schemas to enable reuse and scale.

Agentic SDLC & Engineering Delivery

Own delivery across the full Software Development Lifecycle (SDLC), extending it into a formal Agentic SDLC, including:

Agent design specifications and behavior contracts

Prompt, policy, and tool versioning

Simulation environments and offline evaluation

Automated testing of agent flows and guardrails

Controlled rollout, telemetry-driven optimization, and continuous learning

Build production-grade AI services primarily using Python, integrating:

LLM providers such as Anthropic (Claude), OpenAI, and open-source models

Retrieval-Augmented Generation (RAG) using vector databases (e.g., Pinecone, FAISS, Milvus, Weaviate)

Implement CI/CD pipelines for agent code, prompts, and policies.

Integrate GenAI agents with client systems via APIs, workflow engines, event streams, and data platforms.

Observability, Evaluation & Optimization

Implement agent observability including tracing, decision logging, tool usage, and failure analysis.

Apply evaluation frameworks for hallucination detection, consistency checks, and fitness scoring.

Design feedback loops incorporating human-in-the-loop review and reinforcement.

Monitor cost, latency, throughput, and behavioral drift across deployed agents.

Governance, Risk & Financial Services Compliance

Design Agentic AI platforms aligned with Financial Services regulatory expectations, including:

Auditability and traceability of agent decisions

Model and prompt explainability

Data privacy and security controls

Resilience and fail-safe mechanisms

Embed guardrails and policies addressing hallucination risk, bias, unauthorized actions, and escalation failures.

Produce documentation supporting risk, compliance, internal audit, and regulator engagement.

Team Leadership & Firm Contribution

Provide technical leadership and mentorship to consulting delivery teams.

Contribute to internal GenAI accelerators, agent frameworks, and reusable assets.

Support RFPs, proposals, and client solution designs with credible GenAI and agentic architectures.

Participate in thought leadership on Agentic SDLC, GenAI engineering, and responsible autonomy.

Benefits

This position comes with competitive compensation and benefits package:

1. Competitive salary and performance-based bonuses

1. Comprehensive benefits package

1. Career development and training opportunities

1. Flexible work arrangements (remote and/or office-based)

1. Dynamic and inclusive work culture within a globally known group

1. Private Health Insurance

1. Retirement Benefits

1. Paid Time Off

1. Training & Development

1. Note: Benefits differ based on employee level

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We currently have 700 open roles

Innovation Starts Here

Job Summary

We are seeking a highly skilled Principal AI Engineer to lead the architecture and hands-on development of enterprise agentic AI platforms across core business domains. As a key member of our cross-functional engineering team, you will build and deploy AI copilots and multi-agent workflows for business teams, embed AI directly into enterprise workflows, and ensure seamless integration with ERP and CRM systems.

Key Responsibilities

• Lead the architecture and hands-on development of enterprise agentic AI platforms across core business domains
• Build and deploy AI copilots and multi-agent workflows for business teams (Legal, Finance, Sales, HR, Operations) using Microsoft AI Copilot, SAP BTP, Salesforce, and other platforms
• Embed AI directly into enterprise workflows, ensuring seamless integration with ERP and CRM systems
• Design, implement, and govern secure AI solutions utilizing MCP (Model Context Protocol) and A2A (Agent-to-Agent) orchestration standards
• Develop scalable APIs and microservices in Python and C#, supporting robust, production-ready AI deployments
• Ensure production readiness through best practices in CI/CD, observability, reliability, and continuous evaluation
• Mentor engineers, lead architectural discussions, and collaborate with cross-functional business and technical stakeholders

The Impact You Will Have

• Drive the adoption of agentic AI across Synopsys' core business systems, setting standards for enterprise AI integration and governance
• Deliver high-visibility, high-impact AI solutions that transform business processes and decision-making for teams company-wide
• Shape the architecture and best practices for scalable, secure, and reliable AI across hybrid and multi-vendor environments
• Empower business teams to leverage AI copilots and intelligent workflows for increased productivity and innovation
• Mentor and upskill engineering teams, fostering a culture of excellence, collaboration, and forward-thinking AI adoption
• Ensure AI solutions meet enterprise standards for security, compliance, reliability, and operational excellence

What You’ll Need

• 10–15 years of software engineering experience, with a focus on enterprise systems
• Expert-level proficiency in both Python and C#
• Hands-on experience building and operating production AI/GenAI systems integrated with ERP and CRM platforms
• Deep understanding of agentic AI, RAG, multi-step workflows, and enterprise-grade AI architecture
• Proven experience with Microsoft AI Copilot, Copilot Studio, Microsoft AI Foundry, SAP BTP, and Salesforce AI (including Einstein and agentic capabilities)
• Expertise in microservices, API development, CI/CD pipelines, and cloud deployments
• Experience with SQL, NoSQL, and vector databases
• Preferred: Familiarity with LangChain, LangGraph, LlamaIndex, MCP, A2A, and prior support for business functions such as Legal, Finance, Sales, or HR

Who You Are

• Enterprise-minded engineer with a strong platform and architecture focus
• Hands-on leader who enjoys mentoring and collaborating across business and technical teams
• Pragmatic, delivery-oriented, and able to translate business needs into robust AI solutions
• Adaptable and comfortable working in fast-changing, multi-vendor, and hybrid environments
• Excellent communicator, able to articulate complex technical concepts to diverse audiences
• Committed to continuous learning and keeping pace with the latest in AI and enterprise technology

The Team You’ll Be A Part Of

You will join a cross-functional, forward-thinking engineering team responsible for embedding trustworthy, scalable AI into Synopsys’ most critical business systems. Our team partners closely with business stakeholders and platform owners to deliver agentic AI workflows that create measurable business value. We are passionate about innovation, operational excellence, and setting the standard for enterprise AI adoption.

Rewards and Benefits

We offer a comprehensive range of health, wellness, and financial benefits to cater to your needs. Our total rewards include both monetary and non-monetary offerings. Your recruiter will provide more details about the salary range and benefits during the hiring process.

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As a Gen AI Staff Engineer, you will architect and develop GenAI, RAG, and agentic AI applications for enterprise functions. You will design and deploy AI-powered copilots and multi-step agent workflows using frameworks like LangChain, LangGraph, and LlamaIndex.

Key responsibilities include:

• Building ETL pipelines for document ingestion, parsing, and enrichment, enabling enterprise-scale knowledge integration
• Integrating and experimenting with LLMs and GenAI platforms (OpenAI, ChatGPT, Claude, Amazon Bedrock, LLaMA) for optimal solution fit
• Implementing MCP-based context sharing and A2A integrations to enable seamless interoperability across enterprise applications
• Developing and maintaining robust APIs and microservices for secure and scalable integration
• Implementing CI/CD pipelines and productionization practices for reliable deployments

This role requires a strong understanding of CI/CD pipelines, cloud platforms, and production deployment. You should have experience with microservices, and modern architectural patterns. Familiarity with SQL, NoSQL, and vector databases is also required.

In return, you will have the opportunity to transform business processes across HR, Finance, Legal, and beyond, and enjoy collaborating with cross-functional teams to deliver solutions that matter.

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Honda has a clear vision for the future, and it’s a joyful one. We are looking for individuals with the skills, courage, persistence, and dreams that will help us reach our future-focused goals. At our core is innovation. Honda is constantly innovating and developing solutions to drive our business with record success. We strive to be a company that serves as a source of “power” that supports people around the world who are trying to do things based on their own initiative and that helps people expand their own potential. To this end, Honda strives to realize “the joy and freedom of mobility” by developing new technologies and an innovative approach to achieve a “zero environmental footprint.”

We are looking for qualified individuals with diverse backgrounds, experiences, continuous improvement values, and a strong work ethic to join our team.

If your goals and values align with Honda’s, we want you to join our team to Bring the Future!

Job Purpose

Lead the design, development, and deployment of advanced AI and machine learning solutions supporting Honda’s automotive R&D initiatives, with a focus on production-grade AI for vehicle development, simulation, manufacturing quality, and digital twins,owning solutions end-to-end and mentoring engineers while partnering with CAE, CAD, manufacturing, and data platform teams.

Key Accountabilities

• Lead development and validation of AI/ML solutions with measurable impact for automotive engineering - CAE, and manufacturing use cases.
• Design and deploy AI surrogate models using Graph Convolutional Neural Networks (GCNNs) to augment/replace physics-based CAE.
• Architect and deploy scalable cloud-based AI systems on AWS/Azure aligned with enterprise governance.
• Own the full AI lifecycle: data ingestion, feature engineering, training, evaluation, deployment, and monitoring.
• Implement MLOps and GenAIOps best practices (versioning, drift detection, CI/CD, traceability).
• Develop and deploy agentic AI solutions for CAE in the cloud and deploy AI agents to execute/augment/monitor workflows.
• Support ETL activities related to ADC data (CAE) structure.
• Establish design standards, code quality, and documentation to support reuse and auditability.
• Mentor and technically guide mid-level and junior engineers.

Qualifications, Experience, and Skills

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field, or equivalent experience.
• 8+ years of experience developing and deploying ML/AI systems; 3+ years in production environments.

_Other Job-Specific Skills_

• Hands-on experience with graph neural networks (GCNNs, GNNs, GATs, MPNNs)
• Advanced proficiency in Python; C++ or Java is a strong plus for automotive contexts
• Deep expertise in ML frameworks (PyTorch, TensorFlow, scikit-learn)
• Strong foundation in statistics, optimization, and numerical methods
• Hands-on experience deploying AI solutions on AWS/Azure (e.g., Amazon Bedrock)
• Experience with LangGraph / LangChain & Strands SDK.
• Experience with containers, pipelines, and MLOps tooling (Docker, MLflow, CI/CD)
• Knowledge of model governance, compliance, and responsible AI frameworks
• CAE/physics-informed ML, surrogate modelling, or simulation experience (preferred).
• Prior knowledge of automotive or related design engineering work is a plus.

Job Dimensions

Decisions Expected

Working Conditions

• Work is primarily conducted at an office desk; hybrid (office/home) work may be available.
• Occasional travel and overtime may be required based on project milestones.
• Work in a cross-functional environment supporting engineering, simulation, and manufacturing stakeholders.

What differentiates Honda and makes us an employer of choice?

Total Rewards:

• Competitive Base Salary (pay will be based on several variables that include, but not limited to geographic location, work experience, etc.)
• Regional Bonus (when applicable)
• Manager Lease Car Program (No Cost - Car, Maintenance, and Insurance included)
• Industry-leading Benefit Plans (Medical, Dental, Vision, Rx)
• Paid time off, including vacation, holidays, shutdown
• Company Paid Short-Term and Long-Term Disability
• 401K Plan with company match + additional contribution
• Relocation assistance (if eligible)

Career Growth:

• Advancement Opportunities
• Career Mobility
• Education Reimbursement for Continued learning
• Training and Development Programs

Additional Offerings:

• Lifestyle Account
• Childcare Reimbursement Account
• Elder Care Support
• Tuition Assistance & Student Loan Repayment
• Wellbeing Program
• Community Service and Engagement Programs
• Product Programs

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If you're looking for the chance to leverage advanced technology to redefine the transportation landscape, enhance the customer experience, and improve people's lives: this is the opportunity for you. Join us and challenge your IT expertise and analytical skills to help create vehicles that are as smart as you are.

To meet the growing needs of the Customer analytics business, the team is looking for a self-motivated, technically proficient individual to craft and shepherd coherent solutions. This will require collaboration with a range of stakeholders to clarify requirements, establish pragmatic approaches, and support and articulate decisions over time. You will join a cloud architecture team that works closely with engineering teams and other architects across the organisation.

Responsibilities

Technical Requirements

• Extensive experience with Google Cloud Platform (GCP), specifically BigQuery, Vertex AI, Dataflow, Dataproc, Cloud Run, CloudSQL, Spanner and Apigee.

• Security & Networking: Strong understanding of cloud security protocols, IAM, encryption, and complex network topologies.

• Data Management: Proficiency in Enterprise Data Platforms, Data mesh architecture and data-driven architectural patterns.

• DevOps Tooling: Hands-on experience with GitHub, SonarQube, Checkmarx, and FOSSA.

• Software Engineering: Strong background in building Web Services and maintaining Clean Code standards.

Technical Leadership & Strategy

• System Design: Work with engineering teams to refine system designs, evangelising for horizontal scalability, resilience, and Clean Code compliance.

• Product Collaboration: Partner with Product Managers to decompose complex business needs into incremental, production-ready user stories within an Agile/Sprint methodology.

• Architectural Governance: Assess and document the rationale and tradeoffs for technical decisions; contribute to the broader Cloud Architecture team to improve global practices.

• DevOps Excellence: Utilise and improve CI/CD pipelines using GitHub and automated testing/security tools to maximise deployment efficiency and minimise risk.

Cloud, Networking & Security

• Secure Infrastructure: Serve as the primary architect for cloud solutions, ensuring 'Secure-by-Design' principles are applied across Google Cloud services (Dataflow, Dataproc, CloudRun, CloudSQL, Spanner).

• Advanced Networking: Design and optimise cloud networking configurations, including VPCs, Service Controls, Load Balancing, and Private Service Connect to ensure high availability and low latency.

• Cyber Security Oversight: Integrate security scanning and compliance into the architecture (utilising Checkmarx, SonarQube, and FOSSA). Proactively address vulnerabilities in distributed systems and AI models (e.g., OWASP Top 10 for LLMs).

• API & Data Contracts: Bolster 'Data as a Product' practices by enforcing strict API standards and data contracts to ensure seamless, secure interoperability between services.

• FinOps & Cost Optimisation: Drive fiscal responsibility by right-sizing GCP resources and optimising Generative AI architectures (token management/model selection) to maximise ROI.

• SRE & Performance Tuning: Apply Site Reliability Engineering principles to ensure high availability, minimise system latency, and lead root-cause analysis for complex, distributed system failures.

• DevSecOps & Problem Solving: Integrate security automation into CI/CD pipelines to ensure 'Secure-by-Design' deployments while solving complex architectural trade-offs between speed, scale, and risk.

• Continuous Learning: Stay at the forefront of AI research, specifically regarding autonomous agents, prompt engineering etc

Nice to Have

• AI development tools and frameworks (e.g., LangChain, LangGraph, or Agent Dev Kit) to accelerate the delivery of intelligent applications.

• Agentic & GenAI Design: Lead the architectural design of Agentic AI systems (multi-agent orchestration) and Generative AI solutions, including Retrieval-Augmented Generation (RAG) patterns and LLM integration.

• Kubernetes (GKE): Experience managing containerised workloads at scale.

• Kafka/Event-Driven Design: Experience with high-throughput messaging and event-driven architectures.

• MLOps: Familiarity with the end-to-end lifecycle of machine learning models in production.

Qualifications

You'll have...

• Requires a bachelor's or foreign equivalent degree in computer science, information technology or a technology related field

• 5+ years of Software engineering experience using Java or Python developing services (APIs, REST, etc.)

• 2+ years of experience with Google Cloud Platform or other cloud service provider (AWS, Azure, etc.) and associated cloud components.

• Experience designing/architecting and running distributed systems in a production environment

• STRONG communications skills and cognitive agility - ability to engage in deep technical discussions with customers and peers, become a trusted technical advisor, and maintain good documentation

Even better, you may have...

• Master's degree in computer science, electrical engineering or a closely related field of study

• Familiarity with a breadth of programming languages, platforms, and systems

• Experience with asynchronous messaging and eventually consistent system design

• An agile, pragmatic, and empirical mindset

• Critical thinking, decision-making and leadership aptitudes

• Good organisational and problem-solving abilities

• MDM, Entity Resolution, Customer Analytics and Marketing Analytics experience is a huge plus.

You may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!

As an established global company, we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe, or keep you close to home? Will your career be a deep dive into what you love, or a series of new teams and new skills? Will you be a leader, a changemaker, a technical expert, a culture builder…or all of the above? No matter what you choose, we offer a work life that works for you, including:

• Immediate medical, dental, and prescription drug coverage

• Flexible family care, parental leave, new parent ramp-up programs, subsidised back-up child care and more

• Vehicle discount programme for employees and family members, and management leases

• Tuition assistance

• Established and active employee resource groups

• Paid time off for individual and team community service

• A generous schedule of paid holidays, including the week between Christmas and New Year's Day

• Paid time off and the option to purchase additional vacation time.

For a detailed look at our benefits, click here: Benefit Summary

XML job scraping automation by YubHub

We’re looking for a hands-on ML engineer to prototype and productionize complex classification flows on real production logs, operate prompted classifiers at scale (ad hoc and scheduled), and build secure, compliant data-labeling pipelines.

We’re looking for someone with experience in data pipelines, data science, and machine learning, as well as a strong communicator and great teammate.

The right candidate takes the initiative and enjoys building world-class consumer experiences and products in a fast-paced environment.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more.

As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals.

Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond

Starting January 26, 2026, MAI employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location.

This expectation is subject to local law and may vary by jurisdiction.

Responsibilities:

Build evaluation loops (precision/recall, calibration, drift, human-in-the-loop) and publish dashboards/SLOs.

Generalize machine learning (ML) solutions into repeatable frameworks.

Operationalize prompted classifiers at scale (batch & streaming), including orchestration, autoscaling, monitoring, and cost guardrails.

Conduct thorough review of data analysis and techniques used to summarize the process review and highlight areas that have been missed or need re-examining.

Collaborate cross-functionally with DS, Security, and Platform to define schemas, access patterns, and governance.

Independently write efficient, readable, extensible code and model pipelines.

Commit to a customer-oriented focus by acknowledging customer needs and perspectives, validating customer perspectives, focusing on broader customer context, and serving as a trusted advisor.

Qualifications:

Required Qualifications:

Bachelor’s Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

Preferred Qualifications:

7+ years’ experience writing production-quality Python or Java or Scala code.

5+ years’ experience in distributed systems design and implementation of large scale data processing systems

3+ years’ experience building ML data pipelines using atleast one of AML, Promptflow, Langchain or LangGraph

Demonstrated interest in Responsible AI.

Experience prompting, evaluating, and working with large language models.

#MicrosoftAI #mai-datainsights #mai-datainsights

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We're seeking a hands-on Principal Software Engineer to lead the development of security features and innovative solutions that harness agentic AI to both protect our customers and enable new agentic capabilities in Copilot. You'll design, build, and ship AI-powered defenses, secure orchestration frameworks, and enabling technologies that empower Copilot to act safely and responsibly at scale.

This role demands deep engineering expertise, creativity in applying agentic AI to security challenges, and a passion for building systems that balance innovation with trust. Your work will directly shape how hundreds of millions of users experience safe, trustworthy, and innovative AI. You'll be at the forefront of defining how agentic AI can proactively defend users, mitigate emerging threats, and unlock new secure scenarios,making a global impact on Microsoft's most transformative products.

As a Principal Software Engineer, you will:

• Develop and ship agentic AI-powered security features that proactively protect users from threats such as prompt injection, adversarial manipulation, and abuse of agentic workflows.
• Design and implement secure orchestration frameworks that enable Copilot to safely delegate, coordinate, and execute actions across devices, services, and platforms.
• Invent and apply new intelligent agents that leverage information flow analysis and apply common sense and judgement guardrails for security and privacy.
• Collaborate with product, engineering, security, privacy, and AI teams to drive adoption of agentic security patterns and best practices across Copilot and MAI.
• Establish and monitor key metrics for agentic AI security and innovation, using data-driven insights to continuously improve defenses and enablement.
• Align with central Microsoft security and AI roadmaps, influencing platform capabilities and landing them in Copilot and MAI consumer scenarios.
• Document and evangelize secure agentic AI patterns, ensuring they address novel risks, support safe delegation, and enable responsible orchestration of actions.
• Mentor engineers and foster a culture of secure innovation, balancing rapid development with rigorous protection for customers.

Qualifications:

• Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
• 8+ years in technical engineering roles building large-scale services.
• 6+ years hands-on experience designing and operating security-critical or AI-powered systems at scale, including agentic AI, secure orchestration, or advanced threat defenses.
• Proven ability to design, build, and ship agentic AI features or frameworks.
• Ability to clearly explain complex systems and security concepts to technical and non-technical stakeholders and influence cross-org roadmaps.
• Experience building production agent systems using frameworks such as LangGraph, Amazon Strands SDK, or similar platforms; familiarity with agentic design patterns including tool calling, multi-agent coordination, and secure delegation patterns.
• Hands-on experience with distributed training frameworks (Ray, Slurm, HPC), containerization and orchestration technologies (Docker, Kubernetes) for ML model deployment, and ML lifecycle management in production environments.
• Experience designing evaluation frameworks for LLM-based applications and implementing observability for agent systems using tools such as Phoenix, MLFlow, LangFuse, or custom eval harnesses; understanding of AI safety evaluation methodologies including adversarial testing and red-teaming.
• Experience integrating with Azure AI services, Azure OpenAI Service, or Microsoft security platforms (Azure AD, Defender, Purview).
• Track record of mentoring experienced engineers, driving adoption of secure agentic AI standards across product teams, and influencing technical roadmaps while balancing innovation velocity with fundamentals.

#MicrosoftAI Software Engineering IC5 – The typical base pay range for this role across the U.S. is USD $139,900 – $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 – $304,200 per year.

XML job scraping automation by YubHub

About the Role Copilot for consumers is entering a new era of agentic AI, where intelligent agents act on behalf of users across Windows, Edge, web, mobile, and third-party products. We’re seeking a Senior Software Engineer to help develop security features and solutions that harness agentic AI to protect customers and enable new capabilities in Copilot. You’ll contribute to designing and building AI-powered defenses, secure orchestration frameworks, and enabling technologies that empower Copilot to act safely and responsibly at scale. This role is ideal for engineers who are passionate about applying technical skills to solve security challenges and build systems that balance innovation with trust.

Why This Role Matters Your work will directly shape how hundreds of millions of users experience safe, trustworthy, and innovative AI. You’ll be at the forefront of defining how agentic AI can proactively defend users, mitigate emerging threats, and unlock new secure scenarios, making a global impact on Microsoft’s most transformative products.

Responsibilities Develop and ship agentic AI-powered security features that protect users from threats such as prompt injection, adversarial manipulation, and abuse of agentic workflows. Implement secure orchestration frameworks that enable Copilot to safely delegate, coordinate, and execute actions across devices, services, and platforms. Invent and apply new intelligent agents that leverage information flow analysis and apply common sense and judgement guardrails for security and privacy. Collaborate with product, engineering, security, privacy, and AI teams to adopt agentic security patterns and best practices across Copilot and MAI. Monitor key metrics for agentic AI security and innovation, using data-driven insights to improve defenses and enablement. Document secure agentic AI patterns, ensuring they address novel risks, support safe delegation, and enable responsible orchestration of actions.

Qualifications Required Qualifications: Bachelor’s Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. Preferred Qualifications: 3+ years in technical engineering roles building large-scale services. Hands-on experience designing and operating security-critical or AI-powered systems at scale, including agentic AI, secure orchestration, or advanced threat defenses. Proven ability to design, build, and ship agentic AI features or frameworks Ability to clearly explain complex systems and security concepts to technical and non-technical stakeholders and influence cross-org roadmaps. Agentic AI Development & Orchestration: Experience building production agent systems using frameworks such as LangGraph, Amazon Strands SDK, or similar platforms; familiarity with agentic design patterns including tool calling, multi-agent coordination, and secure delegation patterns Hands-on experience with distributed training frameworks (Ray, Slurm, HPC), containerization and orchestration technologies (Docker, Kubernetes) for ML model deployment, and ML lifecycle management in production environments Experience designing evaluation frameworks for LLM-based applications and implementing observability for agent systems using tools such as Phoenix, MLFlow, LangFuse, or custom eval harnesses; understanding of AI safety evaluation methodologies including adversarial testing and red-teaming Experience integrating with Azure AI services, Azure OpenAI Service, or Microsoft security platforms (Azure AD, Defender, Purview) Track record of mentoring less experienced engineers, driving adoption of standards and best practices across teams, and influencing technical roadmaps while balancing innovation velocity with fundamentals

XML job scraping automation by YubHub

We’re seeking a hands-on Principal Software Engineer to lead the development of security features and innovative solutions that harness agentic AI to both protect our customers and enable new agentic capabilities in Copilot. You’ll design, build, and ship AI-powered defenses, secure orchestration frameworks, and enabling technologies that empower Copilot to act safely and responsibly at scale.

This role demands deep engineering expertise, creativity in applying agentic AI to security challenges, and a passion for building systems that balance innovation with trust.

Your work will directly shape how hundreds of millions of users experience safe, trustworthy, and innovative AI. You’ll be at the forefront of defining how agentic AI can proactively defend users, mitigate emerging threats, and unlock new secure scenarios,making a global impact on Microsoft’s most transformative products.

As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Starting January 26, 2026, MAI employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location. This expectation is subject to local law and may vary by jurisdiction.

Responsibilities:

Develop and ship agentic AI-powered security features that proactively protect users from threats such as prompt injection, adversarial manipulation, and abuse of agentic workflows.

Design and implement secure orchestration frameworks that enable Copilot to safely delegate, coordinate, and execute actions across devices, services, and platforms.

Invent and apply new intelligent agents that leverage information flow analysis and apply common sense and judgement guardrails for security and privacy.

Collaborate with product, engineering, security, privacy, and AI teams to drive adoption of agentic security patterns and best practices across Copilot and MAI.

Establish and monitor key metrics for agentic AI security and innovation, using data-driven insights to continuously improve defenses and enablement.

Align with central Microsoft security and AI roadmaps, influencing platform capabilities and landing them in Copilot and MAI consumer scenarios.

Document and evangelize secure agentic AI patterns, ensuring they address novel risks, support safe delegation, and enable responsible orchestration of actions.

Mentor engineers and foster a culture of secure innovation, balancing rapid development with rigorous protection for customers.

Qualifications:

Required Qualifications:

Bachelor’s Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

Preferred Qualifications:

Master’s Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor’s Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

8+ years in technical engineering roles building large-scale services.

6+ years hands-on experience designing and operating security-critical or AI-powered systems at scale, including agentic AI, secure orchestration, or advanced threat defenses.

Proven ability to design, build, and ship agentic AI features or frameworks.

Ability to clearly explain complex systems and security concepts to technical and non-technical stakeholders and influence cross-org roadmaps.

Experience building production agent systems using frameworks such as LangGraph, Amazon Strands SDK, or similar platforms; familiarity with agentic design patterns including tool calling, multi-agent coordination, and secure delegation patterns.

Hands-on experience with distributed training frameworks (Ray, Slurm, HPC), containerization and orchestration technologies (Docker, Kubernetes) for ML model deployment, and ML lifecycle management in production environments.

Experience designing evaluation frameworks for LLM-based applications and implementing observability for agent systems using tools such as Phoenix, MLFlow, LangFuse, or custom eval harnesses; understanding of AI safety evaluation methodologies including adversarial testing and red-teaming.

Experience integrating with Azure AI services, Azure OpenAI Service, or Microsoft security platforms (Azure AD, Defender, Purview).

Track record of mentoring experienced engineers, driving adoption of secure agentic AI standards across product teams, and influencing technical roadmaps while balancing innovation velocity with fundamentals.

#MicrosoftAI Software Engineering IC5 – The typical base pay range for this role across the U.S. is USD $139,900 – $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 – $304,200 per year.

XML job scraping automation by YubHub

About the Role Copilot for consumers is entering a new era of agentic AI, where intelligent agents act on behalf of users across Windows, Edge, web, mobile, and third-party products. We’re seeking a Senior Software Engineer to help develop security features and solutions that harness agentic AI to protect customers and enable new capabilities in Copilot.

Responsibilities Develop and ship agentic AI-powered security features that protect users from threats such as prompt injection, adversarial manipulation, and abuse of agentic workflows. Implement secure orchestration frameworks that enable Copilot to safely delegate, coordinate, and execute actions across devices, services, and platforms. Invent and apply new intelligent agents that leverage information flow analysis and apply common sense and judgement guardrails for security and privacy. Collaborate with product, engineering, security, privacy, and AI teams to adopt agentic security patterns and best practices across Copilot and MAI. Monitor key metrics for agentic AI security and innovation, using data-driven insights to improve defenses and enablement. Document secure agentic AI patterns, ensuring they address novel risks, support safe delegation, and enable responsible orchestration of actions.

Qualifications Required Qualifications: Bachelor’s Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. Preferred Qualifications: 3+ years in technical engineering roles building large-scale services. Hands-on experience designing and operating security-critical or AI-powered systems at scale, including agentic AI, secure orchestration, or advanced threat defenses. Proven ability to design, build, and ship agentic AI features or frameworks. Agentic AI Development & Orchestration: Experience building production agent systems using frameworks such as LangGraph, Amazon Strands SDK, or similar platforms; familiarity with agentic design patterns including tool calling, multi-agent coordination, and secure delegation patterns. Hands-on experience with distributed training frameworks (Ray, Slurm, HPC), containerization and orchestration technologies (Docker, Kubernetes) for ML model deployment, and ML lifecycle management in production environments. Experience designing evaluation frameworks for LLM-based applications and implementing observability for agent systems using tools such as Phoenix, MLFlow, LangFuse, or custom eval harnesses; understanding of AI safety evaluation methodologies including adversarial testing and red-teaming. Experience integrating with Azure AI services, Azure OpenAI Service, or Microsoft security platforms (Azure AD, Defender, Purview). Track record of mentoring less experienced engineers, driving adoption of standards and best practices across teams, and influencing technical roadmaps while balancing innovation velocity with fundamentals.

#MicrosoftAI Software Engineering IC4 – The typical base pay range for this role across the U.S. is USD $119,800 – $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $158,400 – $258,000 per year.

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

XML job scraping automation by YubHub

We’re seeking a hands-on Principal Software Engineer to lead the development of security features and innovative solutions that harness agentic AI to both protect our customers and enable new agentic capabilities in Copilot. You’ll design, build, and ship AI-powered defenses, secure orchestration frameworks, and enabling technologies that empower Copilot to act safely and responsibly at scale.

This role demands deep engineering expertise, creativity in applying agentic AI to security challenges, and a passion for building systems that balance innovation with trust. Your work will directly shape how hundreds of millions of users experience safe, trustworthy, and innovative AI. You’ll be at the forefront of defining how agentic AI can proactively defend users, mitigate emerging threats, and unlock new secure scenarios,making a global impact on Microsoft’s most transformative products.

As employees, we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Starting January 26, 2026, MAI employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location. This expectation is subject to local law and may vary by jurisdiction.

XML job scraping automation by YubHub

We're looking for a hands-on ML engineer to prototype and productionize complex classification flows on real production logs, operate prompted classifiers at scale (ad hoc and scheduled), and build secure, compliant data-labeling pipelines.

We're looking for someone with experience in data pipelines, data science, and machine learning, as well as a strong communicator and great teammate.

The right candidate takes the initiative and enjoys building world-class consumer experiences and products in a fast-paced environment.

Microsoft's mission is to empower every person and every organization on the planet to achieve more.

As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals.

Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond

Starting January 26, 2026, MAI employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location.

This expectation is subject to local law and may vary by jurisdiction.

Responsibilities:

Build evaluation loops (precision/recall, calibration, drift, human-in-the-loop) and publish dashboards/SLOs.

Generalize machine learning (ML) solutions into repeatable frameworks.

Operationalize prompted classifiers at scale (batch & streaming), including orchestration, autoscaling, monitoring, and cost guardrails.

Conduct thorough review of data analysis and techniques used to summarize the process review and highlight areas that have been missed or need re-examining.

Collaborate cross-functionally with DS, Security, and Platform to define schemas, access patterns, and governance.

Independently write efficient, readable, extensible code and model pipelines.

Commit to a customer-oriented focus by acknowledging customer needs and perspectives, validating customer perspectives, focusing on broader customer context, and serving as a trusted advisor.

Qualifications:

Required Qualifications:

Bachelor’s Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

Preferred Qualifications:

7+ years’ experience writing production-quality Python or Java or Scala code.

5+ years’ experience in distributed systems design and implementation of large scale data processing systems

3+ years’ experience building ML data pipelines using atleast one of AML, Promptflow, Langchain or LangGraph

Demonstrated interest in Responsible AI.

Experience prompting, evaluating, and working with large language models.

#MicrosoftAI #mai-datainsights #mai-datainsights

XML job scraping automation by YubHub

We’re looking for a hands-on ML engineer to prototype and productionize complex classification flows on real production logs, operate prompted classifiers at scale (ad hoc and scheduled), and build secure, compliant data-labeling pipelines.

We’re looking for someone with experience in data pipelines, data science, and machine learning, as well as a strong communicator and great teammate.

The right candidate takes the initiative and enjoys building world-class consumer experiences and products in a fast-paced environment.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more.

As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals.

Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond

Starting January 26, 2026, MAI employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location.

This expectation is subject to local law and may vary by jurisdiction.

Responsibilities:

Build evaluation loops (precision/recall, calibration, drift, human-in-the-loop) and publish dashboards/SLOs.

Generalize machine learning (ML) solutions into repeatable frameworks.

Operationalize prompted classifiers at scale (batch & streaming), including orchestration, autoscaling, monitoring, and cost guardrails.

Conduct thorough review of data analysis and techniques used to summarize the process review and highlight areas that have been missed or need re-examining.

Collaborate cross-functionally with DS, Security, and Platform to define schemas, access patterns, and governance.

Independently write efficient, readable, extensible code and model pipelines.

Commit to a customer-oriented focus by acknowledging customer needs and perspectives, validating customer perspectives, focusing on broader customer context, and serving as a trusted advisor.

Qualifications:

Required Qualifications:

Bachelor’s Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

Preferred Qualifications:

7+ years’ experience writing production-quality Python or Java or Scala code.

5+ years’ experience in distributed systems design and implementation of large scale data processing systems

3+ years’ experience building ML data pipelines using atleast one of AML, Promptflow, Langchain or LangGraph

Demonstrated interest in Responsible AI.

Experience prompting, evaluating, and working with large language models.

#MicrosoftAI #mai-datainsights #mai-datainsights

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About the Role Copilot for consumers is entering a new era of agentic AI, where intelligent agents act on behalf of users across Windows, Edge, web, mobile, and third-party products. We’re seeking a Senior Software Engineer to help develop security features and solutions that harness agentic AI to protect customers and enable new capabilities in Copilot.

Responsibilities Develop and ship agentic AI-powered security features that protect users from threats such as prompt injection, adversarial manipulation, and abuse of agentic workflows. Implement secure orchestration frameworks that enable Copilot to safely delegate, coordinate, and execute actions across devices, services, and platforms. Invent and apply new intelligent agents that leverage information flow analysis and apply common sense and judgement guardrails for security and privacy. Collaborate with product, engineering, security, privacy, and AI teams to adopt agentic security patterns and best practices across Copilot and MAI. Monitor key metrics for agentic AI security and innovation, using data-driven insights to improve defenses and enablement. Document secure agentic AI patterns, ensuring they address novel risks, support safe delegation, and enable responsible orchestration of actions.

Qualifications Required Qualifications: Bachelor’s Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. Preferred Qualifications: 3+ years in technical engineering roles building large-scale services. Hands-on experience designing and operating security-critical or AI-powered systems at scale, including agentic AI, secure orchestration, or advanced threat defenses. Proven ability to design, build, and ship agentic AI features or frameworks. Agentic AI Development & Orchestration: Experience building production agent systems using frameworks such as LangGraph, Amazon Strands SDK, or similar platforms; familiarity with agentic design patterns including tool calling, multi-agent coordination, and secure delegation patterns. Hands-on experience with distributed training frameworks (Ray, Slurm, HPC), containerization and orchestration technologies (Docker, Kubernetes) for ML model deployment, and ML lifecycle management in production environments. Experience designing evaluation frameworks for LLM-based applications and implementing observability for agent systems using tools such as Phoenix, MLFlow, LangFuse, or custom eval harnesses; understanding of AI safety evaluation methodologies including adversarial testing and red-teaming. Experience integrating with Azure AI services, Azure OpenAI Service, or Microsoft security platforms (Azure AD, Defender, Purview). Track record of mentoring less experienced engineers, driving adoption of standards and best practices across teams, and influencing technical roadmaps while balancing innovation velocity with fundamentals.

#MicrosoftAI Software Engineering IC4 The typical base pay range for this role across the U.S. is USD $119,800 – $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $158,400 – $258,000 per year. Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay

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The Machine Learning Platform team at Reddit is a high-impact team that owns the infrastructure that powers recommendations, content discovery, user and content quantification, while directly impacting other teams such as Growth, Ads, Feeds, and Core Machine Learning teams.

Key responsibilities include:

• Contributing to the design, implementation, and maintenance of the LLM Gateway, focusing on features like unified API endpoints for internal/externally hosted LLM, rate/token limit management, and intelligent failover mechanisms to boost uptime and reliability.
• Designing and developing ML and Generative AI systems in cloud-based production environments at scale.
• Building and managing enterprise-grade RAG applications using embeddings, vector search, and retrieval pipelines.
• Implementing and operationalizing agentic AI workflows with tool use using frameworks such as LangChain and LangGraph.
• Driving adoption of MLOps / LLMOps practices, including CI/CD automation, versioning, testing, and lifecycle management.
• Establishing best practices for observability, monitoring, evaluation, and governance of GenAI pipelines in production.

The ideal candidate will have:

• 5+ years of experience in ML Engineering, AI Platform Engineering, or Cloud AI Deployment roles.
• Experience operating orchestration systems such as Kubernetes at scale.
• Deep experience with cloud-based technologies for supporting an ML platform, including tools like AWS, Google Cloud Storage, infrastructure-as-code (Terraform), and more.
• Proficiency with the common programming languages and frameworks of ML, such as Go, Python, etc.
• Excellent communication skills with the ability to articulate technical AI concepts to non-technical stakeholders.
• Strong focus on scalability, reliability, performance, and ease of use.

Benefits include comprehensive healthcare benefits, income replacement programs, 401k with employer match, global benefit programs, family planning support, gender-affirming care, mental health & coaching benefits, flexible vacation & paid volunteer time off, and generous paid parental leave.

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Your responsibilities will include leading the development of agent pipelines, architecting composable agent SDKs with built-in safety and robust fallback strategies, designing tracing tools and alert dashboards to ensure agent performance and quality, owning the agent lifecycle, collaborating closely with security and operations teams to ensure agent governance and auditability, mentoring and upleveling teammates on best practices in observability and resilience, and solving challenging technical problems across the stack to develop critical customer-facing features.

We're looking for engineers who want to shape the next generation of intelligent agents – people who care deeply about building reliable, modular systems and elevating those around them. If you're energized by architecting robust agent SDKs, creating tools that ensure safety and observability, and mentoring others, you'll thrive at Lumos.

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Twilio is undergoing a major business transformation powered by Enterprise AI, supported by a dedicated engineering team building the foundations for a unified, secure, and scalable operating system across GTM functions (Sales, Support, Operations, etc.) as well as Internal non-GTM functions (Finance, HR, Legal, etc.).

Our platform is designed to support a multitude of business functions by deploying intelligent agentic solutions that automate complex workflows and deliver unprecedented user experiences.

We're building the future of work at Twilio, and this role offers the opportunity to be at the forefront of enterprise AI innovation.

This role focuses specifically on transforming how Twilio's Customer Support organization operates through AI-powered tools and agentic products.

We are looking for Full-Stack Engineers who view AI as a fundamental shift in the software development lifecycle of engineering products and the delivery of beautiful, engaging user experiences.

This is an opportunity to deliver innovative software products and solutions across every business function in the company such as Sales, Marketing, GTM, HR, Finance and Legal.

Joining this team means building production-grade, full-stack AI applications. You won’t just be wrapping APIs; you will be engineering the entire lifecycle of agentic applications.

As a Staff Software Engineer within Enterprise AI, you are the technical heartbeat of our products.

Your role is to bridge the gap between bleeding-edge AI research and robust, full-stack production systems.

Responsibilities:

• Co-lead the design and development of our software infrastructure, driving technical vision and strategy to ensure scalability, reliability, and performance.
• Drive the development of sophisticated, stateful web applications.
• Serve as developer leader in distributed systems, data technologies, with strong software engineering skills.
• Drive technical innovation and research to stay at the forefront of emerging data technologies and best practices.
• Mentor and elevate a team of high-performing engineers.
• Collaborate closely with cross-functional teams to understand business requirements and translate them into scalable and efficient technical solutions.
• Continuously adapt to the evolving JavaScript ecosystem to maximize engineering efficiency.
• Ensure data quality, integrity, and security throughout the data lifecycle, adhering to industry best practices and compliance standards.

Qualifications:

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 8+ years of experience in data engineering, software development, or a related field, with at least 3 years in a technical leadership role.
• Experience with full-stack development building web apps, using modern programming languages such as JavaScript, Typescript or React.
• Proven track record of architecting and delivering complex data projects at scale, with a deep understanding of data infrastructure and distributed systems.
• Strong understanding of data modeling, data warehousing, and ETL processes, with experience designing and optimizing data pipelines.
• Excellent communication and collaboration skills, with the ability to influence technical decisions and drive alignment across teams.
• Strong leadership skills, with a track record of mentoring and developing high-performing engineering teams.
• Demonstrated ability to thrive in a fast-paced, dynamic environment and deliver results under tight timelines.

Desired:

• Experience developing production-quality LLM applications and using modern agent frameworks such as Langchain, Langgraph, Llamaindex, LangSmith, LangFuse, CrewAI, and/or others is a plus.
• Expertise in big data technologies such as Hadoop, Spark, Kafka, and cloud-based data services (AWS/GCP/Azure).

What We Offer: Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location. Based on role, employees may also be eligible for additional compensation and benefits, including but not limited to incentive programs, commissions, equity grants, health and wellness benefits, retirement contributions, and paid time off. The estimated pay ranges for this role are as follows:

• $160,320 - $200,400
• Target Bonus Percentage 15% (When Applicable)

The successful candidate’s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location.

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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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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Join the team as our next Staff Software Engineer in the Enterprise AI Engineering team. Twilio is undergoing a major business transformation powered by Enterprise AI, supported by a dedicated engineering team building the foundations for a unified, secure, and scalable operating system across GTM functions (Sales, Support, Operations, etc.) as well as Internal non-GTM functions (Finance, HR, Legal, etc.).

In this role, you'll co-lead the design and development of our software infrastructure, driving technical vision and strategy to ensure scalability, reliability, and performance. You will oversee the integration of complex React-based front-ends with backend modular services, ensuring a seamless UI experience.

As a Staff Software Engineer within Enterprise AI, you are the technical heartbeat of our products. Your role is to bridge the gap between bleeding-edge AI research and robust, full-stack production systems.

Responsibilities:

• Co-lead the design and development of our software infrastructure, driving technical vision and strategy to ensure scalability, reliability, and performance.
• Drive the development of sophisticated, stateful web applications.
• Serve as developer leader in distributed systems, data technologies, with strong software engineering skills.
• Drive technical innovation and research to stay at the forefront of emerging data technologies and best practices.
• Mentor and elevate a team of high-performing engineers.
• Collaborate closely with cross-functional teams to understand business requirements and translate them into scalable and efficient technical solutions.

Qualifications:

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 8+ years of experience in data engineering, software development, or a related field, with at least 3 years in a technical leadership role.
• Experience with full-stack development building web apps, using modern programming languages such as JavaScript, Typescript or React.
• Proven track record of architecting and delivering complex data projects at scale, with a deep understanding of data infrastructure and distributed systems.
• Strong understanding of data modeling, data warehousing, and ETL processes, with experience designing and optimizing data pipelines.
• Excellent communication and collaboration skills, with the ability to influence technical decisions and drive alignment across teams.
• Strong leadership skills, with a track record of mentoring and developing high-performing engineering teams.
• Demonstrated ability to thrive in a fast-paced, dynamic environment and deliver results under tight timelines.

Desired:

• Experience developing production-quality LLM applications and using modern agent frameworks such as Langchain, Langgraph, Llamaindex, LangSmith, LangFuse, CrewAI, and/or others is a plus.
• Expertise in big data technologies such as Hadoop, Spark, Kafka, and cloud-based data services (AWS/GCP/Azure).

Travel:

This role will be remote and based in Colombia. Travel may be required to participate in project or team in-person meetings.

What We Offer:

Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location.

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!

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As the company behind the popular open-source projects , Elasticsearch, Kibana, Logstash, and Beats , we help people around the world do great things with their data. From stock quotes to Twitter streams, Apache logs to WordPress blogs, our products are extending what's possible with data, delivering on the promise that good things come from connecting the dots.

Responsibilities

• Agentic Strategy & Design: Invent and implement sophisticated agentic workflows that use reasoning and tools to complete end-to-end business processes.
• Enterprise Grounding: Apply Retrieval Augmented Generation (RAG) and the Elasticsearch Relevance Engine (ESRE) to ensure agents are deeply grounded in enterprise knowledge for high-accuracy task completion.
• AI Model & Tool Integration: Develop and fine-tune LLMs and integrate them with internal APIs and third-party SaaS tools to enable autonomous action.
• Scalable Infrastructure: Firm understanding of cloud-based environments (AWS, Azure, GCP) in order to support the high-concurrency demands of enterprise agents.
• Lifecycle Management: Oversee the training, deployment, and performance optimization of agents, ensuring they remain secure, reliable, and compliant.
• Technical Leadership: Act as a domain expert on the Elastic Stack, making technical recommendations that push the boundaries of AI-driven productivity.
• Documentation: Maintain comprehensive documentation of AI workflows, cloud infrastructure, and deployment processes.
• Security: Implement standards for security and data privacy to protect sensitive information and ensure compliance with relevant regulations.

Requirements

• 3-5 years of work experience in a relevant field.
• Minimum 1 year experience building with the Elastic Stack.
• Knowledge of Elasticsearch Relevance Engine (ESRE), Jina AI, and advanced RAG patterns is critical.
• Proven success in delivering independent GenAI projects, specifically those involving autonomous task completion or complex workflow automation.
• Agentic Frameworks: Familiarity with LangGraph, LangChain, and LangSmith for building and debugging multi-agent systems.
• Expertise in Enterprise Agentic & Workflow Platforms: Deep familiarity with leading agentic AI and workflow automation platforms (such as Microsoft Copilot Studio, Salesforce Agentforce, ServiceNow AI Agents.)
• Market Trend Integration: Proven ability to apply emerging market trends,such as Multi-Agent Orchestration and Model Context Protocol (MCP),to build high-impact, cost-optimized solutions that scale across the enterprise.
• Programming: Experience with Python or TypeScript for backend logic and agent orchestration.
• Cloud & Orchestration: Familiarity with Kubernetes (Operators/Controllers), Docker, and Terraform for automated deployment.
• Model Expertise: Hands-on experience with LLM providers.

Bonus Points

• Bachelor’s or Master’s degree in Computer Science or a related engineering field.
• Strong communication skills with the ability to translate business requirements into technical agent architectures.
• A commitment to Ethical AI and responsible development practices.
• Experience with containerization and orchestration (e.g., Docker, Kubernetes).
• Knowledge of DevOps practices for model deployment and automation.

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Beyond hands-on development, you will serve as a technical leader: guiding component architecture, mentoring engineers, and driving initiatives that raise the bar for UI quality and frontend engineering practices. This role requires strong ownership, deep problem-solving skills, and excellent communication. You will operate in a small, highly collaborative team where clarity, accountability, and impact matter.

Hands-on experience building AI-powered features and using AI tools to improve engineering productivity is required.

Key Responsibilities:

• Lead by example: contribute high-quality React code and set the standard for frontend craftsmanship across the platform
• Shape architecture: design scalable component systems, state management patterns, and frontend infrastructure that support long-term growth
• Mentor engineers: coach and support teammates through code reviews, design discussions, and problem-solving
• Own complex problems: drive investigation, debugging, and resolution of performance, rendering, and scalability challenges
• Drive execution: translate product and design requirements into clear technical designs and well-scoped Jira tickets
• Collaborate cross-functionally: work closely with product, design, and backend partners to deliver impactful, end-to-end solutions
• Establish best practices: improve standards around code quality, accessibility, performance, and reliability
• Champion improvement: introduce new tools, patterns, or approaches , including AI-enabled workflows , where they add real value

Requirements:

• 7+ years of professional software engineering experience, with a strong focus on building and owning modern frontend applications
• Deep expertise in React and modern JavaScript/TypeScript, including component architecture, state management, and frontend application design
• Experience using AI-assisted development tools such as Claude Code or Cursor to accelerate frontend development and improve engineering productivity
• Strong product and design sensibility, with a high bar for UI quality, usability, consistency, and craft
• Proven track record designing frontend architectures that scale across teams, products, and complex user workflows
• Strong knowledge of performance optimization, accessibility, responsive design, and modern frontend best practices
• Deep debugging and problem-solving skills in browser-based applications, with the ability to quickly identify and resolve issues across frontend-backend boundaries
• Proficiency with GitHub-based development workflows, including pull requests, code review practices, branching strategy, and CI/CD automation using GitHub Actions
• Ability to work effectively with backend systems and APIs, contributing where needed while keeping frontend excellence as the primary focus
• Experience as a technical leader who can drive frontend direction, mentor engineers, and raise the quality bar across the team
• Excellent communication skills and the ability to work closely with design, product, and engineering partners

Nice to Have:

• Experience building or integrating AI-powered features
• Familiarity with LangGraph, LangChain, or similar agent-based frameworks
• Experience with data-rich UIs: dashboards, analytics, or complex data visualization
• Background in design systems or shared component libraries
• Experience with Cypress or end-to-end testing frameworks
• Background in DevOps and CI/CD practices

Within Your First 6 Months:

• 1 Month , Ramp up on systems, ship initial contributions, and build context across the platform and team.
• 3 Months , Own features end-to-end, mentor peers, and influence frontend architecture decisions.
• 6 Months , Lead a major frontend initiative, establish guardrails, and raise the bar on performance, scalability, and engineering practices , including thoughtful use of AI where valuable.

Our Values:

• Humble experts
• Hungry for the opportunity
• Intellectually honest
• Operating as one happy team

Awesome Benefits:

• Discretionary time off & sick days
• Paid holidays
• Health insurance
• 401(k) with employer matching
• Quarterly All-Hands meetings
• And much more!

We are proud to be an equal opportunity workplace committed to building a team culture that celebrates learning, diversity and inclusion.

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Work with purpose.

WorkBoard's Strategy Execution Platform powers the digital operating rhythm for companies around the globe, providing organisation-wide clarity, alignment, and insights for growth. AstraZeneca, Ford, 3M, Intel and many others rely on WorkBoard's platform, playbook, and expertise to accelerate results by aligning OKRs, simplifying business reviews and scorecards, focusing weeklies on outcomes, and leveraging analytics – all with embedded AI. More than 15,000 people are certified in WorkBoard's OKR coaching and Outcome Mindset Methodology which enables their organisations to quickly gain the agility OKRs can provide.

Based in Silicon Valley and founded in 2013, WorkBoard investors include Andreessen Horowitz, SoftBank, GGV Capital, Workday Ventures, M12 (Microsoft), Intel Capital, Silicon Valley Bank, and Capital One.

The Opportunity

As a Full Stack Software Engineer, you will help build and enhance WorkBoard's platform by contributing across frontend and backend systems. You'll work closely with engineering manager, product managers, and designers to deliver features that are scalable, reliable, and impactful for customers.

Experience building AI-powered features or using AI tools to improve development workflows is a plus.

What You'll Do

· Contribute high-quality code across backend and frontend systems · Build and maintain scalable APIs, services, and data models · Collaborate with product and design partners to deliver user-facing features · Participate in code reviews and design discussions with the engineering team · Help investigate, debug, and resolve performance or reliability issues · Translate product requirements into clear technical solutions and well-scoped Jira tickets · Follow and contribute to best practices around code quality, testing, and observability · Explore new tools and approaches,including AI-enabled workflows,where they add value

What You Bring

· 3–5 years of professional software engineering experience with full stack exposure · Strong experience with Node.js and modern JavaScript/TypeScript development · Experience building user interfaces with React and modern frontend patterns · Production experience with PHP and MySQL is plus · Working knowledge of Python for backend services, scripting, or integrations · Familiarity with deploying and operating systems on Azure Cloud · Solid problem-solving and debugging skills across the stack · Strong collaboration and communication skills

Nice to Have

· Solid design principles and coding fundamentals · Experience using AI tools to improve engineering velocity and code quality · Exposure to DevOps and CI/CD practices · Familiarity with LangGraph, LangChain, or similar agent-based frameworks

Within Your First 6 Months

1 Month – Ramp up on systems, ship initial contributions, and build context across the platform and team.

3 Months – Own features end-to-end with support from teammates, contribute actively to design discussions, and deepen full stack expertise.

6 Months – Drive meaningful projects independently, improve engineering practices, and help raise the bar on performance, scalability, and thoughtful AI adoption.

Our Values – We Live By The 4 Hs

· Humble experts · Hungry for the opportunity · Intellectually honest · Operating as one happy team

A Few Of Our Awesome Benefits

· 25 days paid vacation leave · Hybrid work model - we work from the office twice a week · Flexible working hours · Additional Health insurance with Bulstrad Life · Quarterly All-Hands meetings

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Zuma is pioneering the future of agentic AI in property management. We build AI agents that act as property managers, handling the full spectrum of interactions with both prospects and current residents on behalf of our clients.

Our agents don’t just assist human workflows; they own them end-to-end, operating across leasing, collections and resident communications. Zuma has ambitions to continue expanding into adjacent work activities in tangential areas of property management.

This is a rare chance to shape the future of how an entire industry operates , not in theory, but in production, at scale, touching real customers and physical assets every day. At Zuma, human and AI agents work side by side, and you'll help define what that collaboration looks like at its best.

Responsibilities

• Own E2E projects that cross all areas of software development including full stack web apps, agentic AI solutions across multiple work activities, extensive integrations with PMS and CRM systems, infrastructure, and internal tooling.

• Architect, build, and deploy production AI agents using modern agent frameworks, owning the full lifecycle from design to reliability in production.

• Define the technical patterns and standards for how software is built across the engineering org , you will be setting the playbook others follow.

• Strengthen our core systems , including our onboarding/configuration system, integration frameworks, and AI performance analytics infrastructure.

• Collaborate directly with the VPE and product leadership to translate product vision into delivery, making high-stakes technical trade-offs with confidence.

• Own system reliability, observability, and continuous improvement , defining how we measure, monitor, and iterate on our agents and web products in production.

• Work across the stack (backend services, LLM orchestration, integrations, data pipelines, frontends) to ship agents and products that are robust and scalable.

• Tame legacy code and lay down new foundations , patterns and architecture you create will be inherited by the engineers who come after you.

• Be a close partner to the product and operations teams, turning their domain needs into intelligent automated workflows without requiring domain expertise upfront.

Nice to Have

• Prior experience at a startup or high-growth company; comfort shipping fast and iterating in production.

• AWS experience with IaC (Terraform) and comfort working with infrastructure / dev ops.

• Background in building self-serve platforms or integration infrastructure.

• Experience with workflow automation platforms or business process orchestration.

• Experience with telephony integrations (Twilio or similar) and building voice-capable agents or chatbots across text and voice channels.

• Familiarity with speech-to-text, text-to-speech, or real-time audio streaming pipelines in production AI systems.

• Classical ML experience , supervised/unsupervised learning, feature engineering, model training and evaluation outside of LLM contexts.

Our Stack

• Python, TypeScript/Node.js

• OpenAI, Anthropic

• LangGraph, OpenAI Agents SDK, custom orchestration layers

• AWS, AWS ECS, PostgreSQL, Redis

• RealPage, Entrata, Yardi, and other property management systems

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