Ai Systems Engineer Jobs

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. About our Team: Micron’s Industrial and Physical AI team is driving the transformation of semiconductor manufacturing through Autonomous Operations, AI, robotics, and digital twin technologies! We develop and deploy innovative solutions across Micron’s global fabrication and assembly/test facilities, enabling smarter, safer, and more efficient operations at scale. Position Overview: We are seeking a hands-on Full-Stack AI Engineer to design, build, and deploy production-grade AI applications that support Micron's Autonomous Operations initiatives. This role owns the end-to-end development lifecycle, from data pipelines and AI models to APIs, web applications, digital twin integrations, and cloud/edge deployments, delivering impactful solutions for engineers, operators, and business leaders worldwide. Responsibilities: Design, architect, and deliver end-to-end AI products, including data ingestion pipelines, feature engineering, model training/inference, APIs, user interfaces, and application monitoring. Build and maintain modern front-end applications using React, Angular, or Streamlit, supported by backend services in Python and FastAPI. Develop scalable integrations between manufacturing systems, robotics platforms, AMRs, sensor networks, and enterprise applications to enable intelligent factory operations. Design and implement digital twin environments using platforms such as NVIDIA Omniverse, Gazebo, or Unity Robotics Hub to support simulation, validation, and o

We're building the platform that lets long-running autonomous agents operate safely inside NVIDIA's enterprise. These are not assistants on a developer's laptop. They are fleets of agents deployed in the cloud, running continuously at scale on shared accelerated compute. They take on real work across enterprise systems, so people get far more done than they could before. This role defines the constructs that agents are built from: the blueprints they start from, the tools, skills, and plugins that power them against enterprise data, the runtime safety harness that keeps them in bounds, and the connections into credential management, sandbox, memory, and observability. The team designs and ships these building blocks so that agent developers across the company can stand up a new agent, wire it in, and run it for days or weeks. Security and safe execution come out of the box, not something each team has to get right on its own. Today an agent runs inside a single harness. Claude, Codex, and open-source agent harnesses each work differently underneath, with their own execution model, tool interface, and telemetry shape. The platform smooths over those differences, so a single skill, safety policy, or trace works the same no matter which harness is running. We want to enable agents that act on a person's behalf, governed and secure, continuously evaluated and self-improving. These agents coordinate and hand work off to each other, with identity and policy following every hop. They route and tune themselves across harnesses from live eval signals, and get better from their own production telemetry instead of waiting on a human to retrain them. Have you run agents on a harness like Claude or Codex and hit the walls that show up when they run for real, for days, against live systems — and wanted them to learn from it on their own? We're building the platform that solves those problems once, for every team. What you'll b

We are seeking a Staff Engineer to join our growing team to provide technical direction and implement core parts of a new platform we are building to make it easier for customers to build AI applications using MongoDB. As a Staff Engineer on this new team, you will be responsible for providing technical leadership to teams developing cutting edge technologies related to enabling deployment at scale of AI applications. You will take on challenging, high-visibility projects that improve and enhance the performance, scalability, and reliability of the distributed systems infrastructure for this new product. MongoDB engineering teams pride themselves on building high-quality software and living MongoDB cultural values every day. We value intellectual curiosity and honesty, and building together in an environment that prioritizes collaboration over competition. We're looking to speak with candidates based in the New York City area for our hybrid or in-office working models. Position Expectations Work closely with product management, product engineering, product design peers as well as other teams within the company to define the first version and future evolution of the service Design, build and deliver well-tested core pieces of the platform in collaboration with other vested parties Contribute to shaping architecture, code reviews and development practices, developer experience as the teams and product grow Mentor fellow engineers and assume ownership and accountability of projects Qualifications Strong background in building core components for high scale compute and data distributed systems 8+ years experience of building distributed systems, and/or foundational cloud services at scale and an interest in working with Python, Go and Java Proven success in designing, writing, testing, debugging, performance tuning, possessing a strong grip on the foundational materials of computer science and maintaining distributed and/or highly concurrent software s

About the Team DoorDash’s GenAI Platform team sits within Machine Learning Platform and builds the shared infrastructure that helps DoorDash, Wolt, and Deliveroo teams safely bring GenAI-powered products, agents, automation, and personalization to production. Our mission is to increase the velocity of business impact from GenAI. A central pillar of that work is our evaluation platform — the unified evals backbone that lets teams measure, trace, and trust the quality of LLM and agent systems across the company, powering trace/score ingestion, LLM-as-judge workflows, agent simulations, and LLM observability for the tens of millions of daily requests flowing through our LLM Gateway. We also own core platform surfaces including the Agent Gateway, open-weights model serving and batch inference, guardrails, and cost attribution. About the Role You will join a small, high-leverage team building production infrastructure for Generative AI at DoorDash, with a primary focus on our evals and LLM observability platform: the systems that let teams evaluate, trace, and continuously improve the quality of LLM and agent products. You’ll work across evaluation frameworks and SDKs, OpenTelemetry-based trace/score ingestion, LLM-as-judge and offline/online eval pipelines, agent simulations, data pipelines, backend services, and observability. This role is ideal for an engineer who enjoys building reliable measurement and quality primitives in a fast-moving technical area where product needs, model capabilities, vendor ecosystems, and evaluation methodologies are evolving quickly. You’re excited about this opportunity because you will… Build the infrastructure that helps DoorDash teams move GenAI ideas from prototype to production, increasing the velocity of business impact from AI across the company. Work on our unified evals platform — evaluation SDKs, OpenTelemetry trace/score ingestion, LLM-as-judge, offline and online eval pipelines, and agent simulations — alongside the LLM Gatew

Overview: We are looking for a Product Manager to support the build, rollout, adoption, and continuous improvement of AI-powered products used across Guidepoint’s expert-network operations. This role sits at the intersection of product management, product operations, workflow automation, AI adoption, and internal tools. The ideal candidate is a hands-on problem solver who can work closely with users, engineering, QA, design, operations, and leadership to turn high-friction workflows into reliable, scalable product systems. The Product Manager will support a portfolio of mature and emerging initiatives by writing clear requirements, managing user feedback, looking at adoption, usage data & analytics, triaging issues, supporting UAT and helping teams make data-driven product improvements. This role is especially important as Guidepoint expands its use of AI, automation, and human-in-the-loop workflows across complex operational processes. What You’ll Do: Product Delivery & Execution Partner with engineering, QA, UX, and business stakeholders to support timely and high-quality delivery of product improvements. Participate in sprint planning, backlog refinement, UAT, release readiness, and post-release review. Help ensure features are tested against real user workflows, edge cases, business rules, and operational expectations. Support rollout planning, user onboarding, training, and adoption follow-ups for new and existing product capabilities. Product Operations & Workflow Support Act as a day-to-day product contact for users Triage bug reports, user questions, change requests, and product feedback. Translate recurring themes into clear product requirements, tickets, acceptance criteria, and follow-up actions. Maintain strong product hygiene across Jira, Confluence, release notes, user documentation, and training materials. AI Workflows & Tools Work with product and engineering teams to ensure AI-driven features are usable, measurable, and aligned with

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role You will build the low-level device runtime that turns compiled programs into efficient, functional and performant execution on OpenAI’s custom AI accelerator. This software will schedule kernel launches, manage device memory and address spaces, coordinate synchronization, and expose reliable abstractions to higher-level runtimes and frameworks. You will work at the boundary of software and hardware, partnering with compiler, kernel, architecture, verification, and silicon teams to define interfaces and validate behavior. You will also use and improve event-based, cycle-accurate simulation to develop runtime capabilities before silicon is available, diagnose performance and correctness issues, and guide hardware-software co-design. In this role, you will: Design and implement the low-level device runtime for OpenAI custom silicon. Build kernel-launch scheduling, command submission, queueing, dependency tracking, and completion handling. Manage device memory spaces, allocation, virtual-to-physical mappings, data movement, and lifetime across concurrent workloads. Implement synchronization primitives, events, barriers, streams, and ordering guarantees that are correct and efficient. Define clean interfaces between the runtime, drivers, firmware, compiler-generated code, kernels, and higher-level execution systems. Use event-based, cycle-accurate simulators to develop, validate, debug, and performance-tune runtime behavior before and after silicon availability. Di

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. What you’ll be doing: Use and develop AI-powered tools to make software testing smarter, faster, and more effective! Improve test case generation, defect detection, flaky test analysis, regression testing, and test coverage optimization. Work with product, engineering, and cross-functional teams to review requirements and define test strategies. Build test plans, design and execute test cases, and report quality status, risks, bugs, and results. Perform functional, performance, fault-injection, reliability, and regression testing for cloud-native systems. Automate test cases and contribute to scalable test frameworks. Manage the bug lifecycle, reproduce customer issues, and verify fixes. What we need to see: MS or PhD in Computer Science, Engineering, or a related field. 5+ years of QA, test automation, or software testing experience. Hands-on experience using AI tools to improve QA workflows. Strong QA fundamentals, test strategy, test planning, and failure analysis skills. Proficiency with Unix/Linux and shell or Python programming. Exp

Drata is building the trust layer between great companies - automating compliance, managing risk, and helping organizations prove trust continuously as they scale. We're Dratanauts: a global crew of 600+ professionals united by a culture that rewards integrity, ownership, and raising the bar, no matter where in the world we're working from. Why Join the Drata Team? At Drata, you're not maintaining legacy compliance software - you're building the agentic AI platform defining what trust looks like for the next generation of companies. Here's what makes the work itself worth showing up for: Problems without a playbook: You'll work at the edge of AI and security, building agentic governance, continuous compliance, and real-time trust verification to solve problems that don't have an established answer yet. You're writing it as you go. Real ownership, not just process: Our values center on owning outcomes and raising the bar, not checking boxes. You're expected to have opinions and back them. A seat at the table: Your perspective is unique and valued. Open debate and diverse viewpoints are built into how decisions actually get made here, at every level. Growth at rocketship speed: Drata is scaling fast, which means scope grows fast too. High performers get more ownership, visibility, and experience. A crew, not just coworkers: Dratanauts consistently describe a "come as you are" culture with sharp, curious people—the kind of team that makes hard problems genuinely fun to solve. See what they say here and follow us on LinkedIn for company news, employee stories, and career updates. Job Summary: Drata's AI Platform team builds the production infrastructure that powers AI features across our compliance platform — from MCP servers that make Drata's data available to AI agents, to LLM workflow orchestration that automates SOC 2, TPRM, and policy analysis. You'll own the systems that sit between our AI models and our customers: tool definitions that agents actually understand,

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the Role This isn’t a typical engineering role. You won’t be embedded in a single product team or siloed in one product area. Instead, you’ll sit within Platform Engineering, own the AI-assisted coding domain, and work across all of engineering at Sentry, focused specifically on how AI coding agents participate in our software development lifecycle. For AI coding agents to work well in our repo, the internal systems they depend on need to be accessible via API, not locked behind UIs that require human interaction. Right now, many of those systems aren’t agent-ready. You’ll audit and prioritize that gap, expose those systems programmatically, and build the connections that let tools like Claude Code operate on them end-to-end. From there, the scope expands to improving the quality of AI-generated pull requests and automating the engineering work that’s important but consistently deprioritized. You will look from context engineering standpoint to see what to send to our model; you will look from harness engineering standpoint to see the tools it can use, the permissions it has, the state it carries forward, the tests it has to pass, the logs you capture, the retries, checkpoints, guardrails, and evals. You’ll work closely with the dev infrastructure team as your home base, then collaborate across every product team coding in our repo once the tooling foundation is in place. It’s a broad role with real impact, and the work you do will directly change how Sentry engineers ship software. What You’ll Do Audit Sentry’s internal developer systems and make them API-ready for AI agents. You’ll prioritize and drive the work of ex

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. The Cortex CoWork team is defining the future of AI for enterprise data. Our mission is to transform how the world’s largest enterprises interact with their data through flagship products like Snowflake (CoWork) Intelligence . As a Principal AI Engineer , you will be a technical North Star for our AI initiatives. You won't just execute on a roadmap; you will help define it. You will tackle the most complex, "frontier" problems in agentic reasoning, NL-to-SQL, and enterprise-scale RAG, ensuring our AI products are not only innovative but fundamentally reliable and scalable for the Fortune 500. What you will do in this role: Technical Strategy & Architecture: Define the long-term technical vision for Snowflake Intelligence. Lead the architectural design of multi-agent systems, complex tool-use frameworks, and self-correcting NL-to-SQL engines. Drive Industry-Leading Reliability: Move beyond simple evals to build world-class, automated "hill-climbing" infrastructure. You will establish the methodology for how Snowflake measures and guarantees LLM performance across diverse customer schemas. Cross-Functional Influence: Partner with Product and Engineering leadership to align AI capabilities with business goals. You will bridge the gap between Research (modeling) and Product

We're looking for a Senior Software Engineer to integrate and improve our AI developer experience so that engineers at Asana can use AI to increase their velocity. As part of the AI Developer Productivity team, you'll build the next generation of AI-powered developer tools across editors, IDEs, CLIs, code review, and cloud and local coding agents.This role is based in our New York City office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. What you’ll achieve Design and build AI-augmented workflows and systems that help coding agents understand the codebase, follow engineering practices, and enable Asana engineers to complete software development tasks faster and with more confidence. Design and scale autonomous cloud agents that take on complex, multi-step engineering tasks to reduce toil and enable engineers to focus on higher-leverage work. Build and refine IDE, editor, and CLI integrations that make AI-assisted development feel intuitive in engineers' daily work. Create reusable agent skills, tools, context, and integrations that teams across Asana can build on rather than reinvent. Improve AI-assisted code review workflows so engineers get faster, higher-quality feedback before and during review. Drive adoption of AI developer tools across engineering through usability improvements, measurement, documentation, and enablement. About you 5+ years of working in large codebases Experience building developer tools, internal platforms, infrastructure, IDE/editor integrations, CLIs, or workflow automation. Hands-on experience with AI-assisted development tools (such as Cursor, Claude Code, or Codex), or extending coding agents, MCP-based int

The AI platform is responsible for all AI infrastructure across Datadog. Our mission is to provide tools and platforms that enable data scientists and engineers to conduct large-scale training and inference with ease. We support products such as Bits AI , LLMObs and all our AI research . As an engineering manager for the Training & Serving team, you’ll join a new and fast growing team and organization. You will support building and scaling the team, define our technical vision and help shape the roadmap. Your team will lead the charge on multiple critical technical challenges: distributed training of foundation models, serving at scale, designing the user experience. You’ll work closely with sister teams in the AI platform organization ensuring a seamless AI development cycle. You’ll also partner with the Applied AI org and with Datadog infrastructure & tooling teams to build out systems from the ground up. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Manage and grow the Training & Serving team, directly managing 10+ engineers Define our technical roadmap in alignment with AI platform goals and the Applied AI team roadmap. Work with our core platform teams to tailor Datadog's storage, infrastructure and data pipelines to our needs Create a strong team culture aligned with our engineering standards and our customer focus Participate in hands-on work: Code reviews, design reviews and some coding Who You Are: Previous experience (1+ years) leading software engineering teams, as a tech lead or people manager Strong technician with a mix of backend, data engineer and infrastructure experience who is interested in remaining a hands-on leader Excellent leader with strong

Engineering Manager, AI Conversation Platform Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team The newly formed Conversation Platform team aims to build a conversation platform for all merchants who use Stripe. We are doing so by (a) automating the easy tasks, and (b) assisting our users in the difficult tasks. Some examples include customizing the Stripe landing page to suggest bespoke integrations, allowing users to command the Stripe API in natural language, and resolving user issues automatically. We are developing RAG based systems on the latest LLMs as well as fine-tuning our own models. We’re an end-to-end team going from ideas to models to shipping in production. What you’ll do Responsibilities Driving an ambitious vision for AI/ML that benefits our users Setting the technical & process direction for the team based on business goals Brainstorm and coordinate product integrations with partner teams Proposing new ideas and building prototypes Be an integral part of a larger ML community internally & externally Hire & develop a world-class team to deliver high-quality ML systems. Coach engineers to help them grow in their careers and maintain a high bar Who you are We are looking for ML Engineering Managers who are passionate about using ML to improve products and delight customers. You have experience leading teams that develop streaming feature pipelines, build ML models, and deploy them to production, even if it involves making substantial changes to backend code. You a

About the Team OpenAI's mission is to ensure that AGI benefits all of humanity. The Business Systems team helps make that mission possible by building the internal products and platforms that allow OpenAI to operate with speed, reliability, and care. We build internal applications and workflows for Finance and Supply Chain. Our work spans product discovery, React and TypeScript interfaces, Python services and APIs, data models, workflow orchestration, enterprise integrations, and the systems that connect people to systems of record. We work directly with the people who use these products and care about correctness, permissions, auditability, and production reliability. Examples of our work include building an integration platform for supply chain integrations, integrations with Oracle Fusion and Zip, contract intelligence applied to B2B revenue recognition, and Temporal-based agentic workflows for credit checks, duplicate bank detection, and invoice triaging. We turn these efforts into reusable patterns that can support many workflows, rather than one-off automations. About the Role We are looking for Product Engineers to build internal applications end to end. This role spans product discovery, user experience, frontend, backend services, data models, workflow orchestration, and integrations with order management, fulfillment, and supply chain systems. You will take a problem from a first conversation with a Finance or Supply Chain partner through design, implementation, rollout, and production support. Strong candidates combine product judgment with engineering depth. You should be comfortable moving between a React interface, a Python API, a durable workflow, and an integration with an enterprise system. You should be able to ship a useful first version quickly while building the foundations for reuse, security, and long-term maintainability. Direct AI experience is helpful, but the core requirement is strong product engineering judgment and reliable execution. I

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Cloud Support Engineer — AI/ML & Programmability (Night Shift) Location: Pune, India Snowflake's Support team is expanding. We're looking for a Cloud Support Engineer who enjoys working with data and solving a wide variety of problems, drawing on hands-on experience across operating systems, database technologies, big data, data integration, connectors, and networking. Our mission is to make Snowflake the preferred platform for running all AI, ML, data science, and data engineering workloads. You'll join a highly productive, fast-moving team supporting Snowflake Cortex and our ML product lines — work that is central to delivering on Snowflake's AI Data Cloud mission. Snowflake Support is committed to providing high-quality resolutions that help customers deliver data-driven business insights and results. We are a team of subject matter experts working collectively toward our customers' success, building partnerships by listening, learning, and connecting. Snowflake's values shape how we deliver world-class Support: putting customers first, acting with integrity, owning initiative and accountability, and getting it done. As a Cloud Support Engineer, you'll be the technical partner our customers turn to for guidance on using Snowflake effectively. You'll also be the voice