Ai Systems Engineer in United States

About the Team The Ecosystem AI Deployment Engineering (ADE) team supports strategic partners as they build high-quality technical integrations into ChatGPT and Codex. Our goal is to create products users depend on, drive adoption and retention, and build an ecosystem where partners win when OpenAI wins. About the Role We are looking for an AI Deployment Engineer to help strategic partners design, build, evaluate, submit, launch, and maintain high-utility plugins for ChatGPT and Codex. This is a hands-on, partner-facing product engineering role for someone who can contribute to the platform itself, lead sophisticated partner engagements, and translate ambiguous product needs into production-ready integrations. You will work across partner product and engineering teams and OpenAI's product, engineering, partnerships, legal, policy, design, and go-to-market teams. You will identify the right use cases, prototype and review implementations, run evaluations, debug issues across systems, guide partners through submission and review, and support launch and post-launch iteration. The best person for this role moves fluidly between code, product judgment, project leadership, and clear communication with engineers and executives. This role is a fit for a product minded engineer who wants to stay close to users and partners while still going deep on code, reliability, evaluations, and developer experience. The goal is to help partners ship plugins that are not merely technically functional, but genuinely useful in ChatGPT and Codex. This role is based in our San Francisco office. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Own the technical partner journey for priority B2B plugins—from pitch and readiness assessment through architecture, build, evaluation, submission, launch, and ongoing maintenance. Identify strong plugin use cases, define crisp user journeys and expected behaviors, and

OpenAI’s charter calls on us to ensure the benefits of AI are distributed broadly and safely. Our Health AI team focuses on expanding access to high-quality medical expertise and aims to set a high standard for deploying AI responsibly in high-stakes domains. Improving health will be one of the defining impacts of AGI. Today, millions of people lack access to reliable medical information, and clinicians around the world face increasing time and resource constraints. We are building AI systems that support patients, clinicians, and health workers, while meeting the highest standards for safety, reliability, and privacy. We are seeking full stack software engineers to help build and scale products used by consumers and care providers globally. You will work closely with product, design, and research teams to ship real systems in a fast-moving, high-impact environment. In this role, you will: Design and build scalable fullstack systems for consumer and enterprise health. Own end-to-end feature development—from early design and implementation through deployment, monitoring, and iteration. Build and maintain data pipelines and services that meet strict privacy, security, and compliance requirements (e.g., HIPAA). Collaborate closely with researchers and safety teams to integrate reliability, evaluation, and guardrails into production systems. Debug, optimize, and harden systems to support high availability, performance, and global scale. Take ownership of ambiguous problems and drive them to practical, high-quality solutions. You might thrive in this role if you: Are deeply motivated by improving health outcomes and expanding access to medical expertise. Are a strong engineer who enjoys building durable, well-designed systems. Have 5+ years of experience writing maintainable, production-quality code. Can operate with high agency—owning problems end-to-end with minimal supervision. Enjoy working in fast-moving, cross-functional teams with engineers, product managers, desi

Applied AI is where Datadog's ambitious AI bets get built and shipped ( Bits Chat , updog ). We sit at the intersection of research and product: turning promising capabilities from Datadog AI Research lab and the research community into production systems that reach real customers. The team builds the foundations for agentic systems capable of operating at scale in complex production environments. Current bets span agents that run autonomously at scale, context and memory layers that make those agents more intelligent over time, and tools that help customers build and validate AI-native services in production. The mandate is to move fast from idea to customer impact, and when a product finds its footing, to set it up for growth. As an Engineering Manager I in Applied AI, you will lead a team of engineers and applied scientists working on one of these challenges. You will define technical direction, run short feedback loops, make deliberate decisions about what to pursue or stop, and work closely with product managers, research teams, and cross-functional partners to ship AI capabilities that matter. At Datadog, we place value in our office culture, the relationships and collaboration it builds and the creativity it brings. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do Lead and develop a team of engineers and applied scientists focused on building the foundations for agents operating at scale Work closely with product managers, research teams, and cross-functional partners to shape the team's bets from initial framing through to broader adoption, with a clear definition of success criteria at each stage Own end-to-end delivery of high-quality AI systems, from early research exploration to production-grade reliability, with high standards for operational excellence, system reliability, and technical quality Navigate the unique challenges of shipping AI-powered products: balancing quali

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. At Snowflake, we are building a high-impact team to help the world's most innovative companies unlock the power of AI. As an Forward Deployed Engineer, Applied AI on our Cortex AI team, you will be a hands-on builder and a key technical partner to our most strategic customers, placing you at the forefront of the enterprise AI revolution. You won't just work with cutting-edge technology – you'll deploy it to solve real-world business problems at scale, building production-grade AI systems using Snowpark, Cortex, and our native LLM capabilities. IN THIS ROLE AT SNOWFLAKE, YOU WILL: Build Customer Solutions : Architect, build, and deploy enterprise-grade AI solutions, including sophisticated AI agents. Own the end-to-end lifecycle of your work streams – from prototype to production – directly solving customers' most complex business challenges. Own the Quality of What You Ship : Define what "good" means for the systems you build. Translate ambiguous customer goals into measurable quality metrics, evaluation frameworks, and golden datasets – then run systematic eval loops to hill-climb on agent quality, catch regressions before customers do, and continuously raise the bar on accuracy, faithfulness, and safety. Treat measurement as a first-class part of building, not an aftertho

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. About the AI Products team The AI Products team is part of the broader Marketplace & Collaboration organization and is focused on bringing AI products on top of Snowflake’s data and application platform to help customers discover, share, monetize, and act on data assets & applications more easily. This team is building the connective tissue of the agentic enterprise: the infrastructure and product surfaces that allow Snowflake customers to seamlessly share datasets, semantic views, and applications, and make them discoverable and executable through Cortex Code, CoWork, and other agentic harnesses. Our strategy is centered on evolving Snowflake Marketplace for the AI era, including packaging data and intelligence into ready-to-use agentic experiences, and enabling governed access patterns that let AI systems safely operate on enterprise data and applications. As a Staff Software Engineer on AI Products, you will Lead the design and delivery of large, complex initiatives spanning multiple teams, turning ambiguous product and platform opportunities into durable technical solutions. Shape the architecture for how datasets, applications, semantic assets, and agentic capabilities are shared, discovered, governed, and invoked across Snowflake surfaces and third-party agent

About the Team OpenAI develops models that can reason through complex problems and hardware designed for the demands of advanced AI. AI for Chips connects these efforts: applying increasingly capable AI systems to the work of semiconductor engineering. Our goal is to help engineers develop better chips and shorten design cycles. This work brings research, model training, and hardware expertise together to build tools that engineers can use on real designs, with correctness and measurable performance at the center. About the Role We’re hiring a Research Engineer to help OpenAI models solve chip-design problems through reinforcement learning, tool use, and evaluation. You’ll own experiments from the initial idea through implementation and analysis. That means building environments and evaluations, running training, investigating failures, and using the results to decide what to try next. You’ll also build the software needed to make those experiments reliable and reproducible. We value strong coding fundamentals, careful experimental judgment, and the ability to make progress independently. Prior chip-design experience is helpful, but you can learn the domain alongside the team’s hardware specialists. In this role, you will: Build RL environments and evaluations for tasks such as RTL generation, design verification, and physical design optimization. Develop and test approaches that help models use chip-design tools and improve power, performance, and area while preserving correctness. Design experiments, establish baselines, and measure whether improvements hold up on new tasks and designs. Investigate failures across model behavior, rewards, evaluation tools, and experiment infrastructure. Improve iteration speed through better tooling, faster evaluations, and proxy rewards that reflect the outcomes we care about. Turn successful experiments into reusable research code and training workflows, working closely with researchers and engineers. You might thrive in this ro

About the Team OpenAI develops models that can reason through complex problems and hardware designed for the demands of advanced AI. AI for Chips connects these efforts: applying increasingly capable AI systems to the work of semiconductor engineering. Our goal is to help engineers develop better chips and shorten design cycles. This work brings research, model training, and hardware expertise together to build tools that engineers can use on real designs, with correctness and measurable performance at the center. About the Role We’re hiring a Software Engineer to build the research infrastructure and tooling that help OpenAI models design silicon. You’ll turn chip-design workflows into reliable environments for reinforcement learning and evaluation, and make it easier for researchers to run experiments and iterate on new ideas. You’ll move between software engineering, tool integration, and open research problems. We value strong coding fundamentals, clear technical judgment, and independent execution. Prior chip-design experience is helpful, but you can learn the domain alongside the team’s hardware specialists. In this role, you will: Build and maintain infrastructure for reinforcement learning environments, evaluations, and long-running experiments. Integrate electronic design automation (EDA) tools into workflows for RTL generation, verification, and physical design optimization. Improve experiment reliability, reproducibility, observability, and performance; debug failures across tools, services, and infrastructure. Develop tooling and model harnesses that let researchers test ideas quickly and measure correctness and power, performance, and area (PPA). Collaborate with researchers and engineers to turn successful experiments into reusable systems and training workflows. Own ambiguous projects end to end, communicate progress, and use results to guide the next iteration. You might thrive in this role if you: Have strong software engineering fundamentals, with

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . As a Staff Software Engineer on the Core Automation team within the Platform group, you'll architect and build the Agentic AI systems that are transforming how Coinbase operates. This team is reimagining customer support and compliance processes for a fully AI-driven world, designing intelligent agents, orchestration frameworks, and measurement systems that deliver delightful customer experiences at scale. You'll own the technical direction for production AI systems, working across cross-functional teams to bring this vision to reality while building primitives that scale automation across the company. What you'll do: Architect and build Agentic AI systems that power Coinbase's compliance automation and other Operations, from intelligent agents through orchestration and guardrails Design foundational APIs and measurement frameworks that ensure AI agents are grounded, relevant, and reliably deliver customer delight with minimal hallucination Lead technical direction for distributed systems underpinning AI automation, defining architecture patterns and strategic roadmaps in partnership with engineering leadership Build reusable primitives and orchestration solutions that enable AI-powered automation to scale across multiple domains beyond the initial customer support and compliance focus Mentor engineers on AI system design techniques, coding standards, and production-

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 is seeking a Senior Applied AI Engineer to drive the quality and effectiveness of our AI systems through rigorous experimentation, evaluation, and applied research. This is a research-focused role emphasizing experimentation and rigor over production engineering. You'll own the science behind how Drata's AI products retrieve, reason, and respond — and you'll work closely with

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 As a Senior Software Engineer on Sentry’s AI/ML team, you’ll be responsible for building the evaluation infrastructure that measures the accuracy, reliability, and real-world performance of our AI systems. This role is critical to ensuring that our debugging agents and AI-powered features behave correctly, safely, and predictably as they scale. You’ll design datasets, benchmarks, and test harnesses that turn ambiguous AI behavior into measurable signals, helping the team ship AI with confidence. In this role you will Design and build robust evaluation frameworks to measure accuracy, reliability, regressions, and edge cases in AI systems Create and curate high-quality datasets, golden test cases, and benchmarks grounded in real production data Build automated test harnesses and metrics pipelines to continuously evaluate models, prompts, and agentic workflows Partner closely with applied AI engineers and product leaders to define what “good” looks like and translate it into measurable criteria Own the evaluation lifecycle for major AI initiatives, from early experimentation through production monitoring You’ll love this job if you Care deeply about correctness, rigor, and measurement in AI systems Enjoy turning fuzzy product goals and model behavior into concrete tests and metrics Like building foundational infrastructure that unlocks faster iteration and higher confidence for the entire AI team Thrive in cross-functional environments and enjoy influencing model design through better evaluation Qualifications Minimum 5+ years of professional experience with a Bachelor’s degree in computer science, machine learni

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. Senior Director, Generative AI About the Role Roblox Build is our generative creation product, the platform where creators design, build, and publish 3D experiences. We are looking for a Senior Director of Generative AI to lead the Applied AI organization inside Build, responsible for turning state-of-the-art foundation models into high-quality, reliable creation systems at Roblox scale. This leader will own the full applied AI stack: model strategy and routing, model adaptation and fine-tuning, code generation (CodeGen), 3D layout generation (LayoutGen), and the evaluation science and infrastructure that tells us what actually works. You Will Own model strategy and routing for Build. Design and build an intelligent model layer that selects the right model for each creation task based on quality, capability, latency, cost, and safety, leveraging both frontier models and Roblox-adapted open-source models. Lead model adaptation across the Applied AI org, including fine-tuning, distillation, synthetic data generation, human feedback pipelines, and preference optimization for Roblox-specific creation tasks such as Luau code generation and 3D scene understanding. Drive CodeGen capabilities

About the Team OpenAI’s Infrastructure Operations team is responsible for the availability, reliability, and operational excellence of one of the world’s largest AI infrastructure networks. The team owns day-to-day operations of production AI networks across Industrial Compute's data centers, working with colocation providers, deployment teams, and hardware vendors to deliver highly available GPU infrastructure for AI training and inference workloads. About the Role We are seeking an Infrastructure Operations Engineer to operate and improve the large-scale Ethernet fabrics that support GPU clusters, storage systems, and management infrastructure. This role combines hands-on production operations with automation, observability, and incident response across a global AI network. The ideal candidate has experience operating high-availability data center, cloud, AI, or HPC networks and can move comfortably from physical-layer troubleshooting to routing and fabric behavior, change execution, and root-cause analysis. You will partner closely with network architecture, systems engineering, GPU engineering, storage engineering, security, deployment, site operations, service providers, colocation partners, and hardware vendors to raise reliability and reduce operational toil. Key Responsibilities Own the operational health, availability, and reliability of production AI network infrastructure across Industrial Compute's data centers. Monitor, troubleshoot, and resolve network incidents while meeting service-level objectives (SLOs), reducing Mean Time to Detect (MTTD), and minimizing Mean Time to Recovery (MTTR). Operate and maintain large-scale Ethernet fabrics supporting GPU compute, storage, and management networks. Execute production network changes, maintenance windows, and capacity expansions with minimal customer impact. Manage the hardware lifecycle, including switch and optics replacements, RMA coordination, software upgrades, and preventive maintenance. Support new A

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 We are looking for a systems-minded engineer to help advance our kernel development, performance engineering, and hardware-software co-design capabilities, with a particular focus on AI-assisted workflows and tooling. This person will work at the intersection of kernel optimization, developer tooling, observability, and research infrastructure, helping us improve both how production kernels are built and optimized, and how future hardware-software systems are designed and evaluated. The role is ideal for someone who is excited by low-level performance work, but also sees AI and automation as powerful tools for accelerating engineering velocity. You will help define the future of kernel engineering in the era of AI-assisted development. In this role, you may: Build developer tooling and workflows that make kernel development and performance optimization faster, more scalable, and easier to debug, integrate, and deploy. Develop observability, diagnostics, and validation infrastructure that makes AI-assisted optimization systems more interpretable, reliable, and effective. Optimize production kernels end to end by formulating optimization problems, running search loops, analyzing bottlenecks, debugging generated implementations, and landing improvements into production. Design abstractions, interfaces, and automation systems that accelerate kernel optimization, correctness validation, and hardware-software co-design. Improve AI-assisted optimization systems for sp

At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. As a Senior Applied AI Engineer at Vanta, you will play a crucial role in shaping Vanta’s AI offerings, setting technical strategy, and leading projects that leverage AI to deliver smarter, faster outcomes for our customers. You'll be part of a team integrating AI into the Vanta product, working alongside a multidisciplinary group of product engineers, machine learning engineers, product managers, designers, and security and compliance experts to implement, scale, and maintain AI-enabled product experiences. In this role, you’ll build products that enable Vanta’s customers to leverage AI to accelerate their journey towards compliance, managing risk, and earning trust. Visit our Vanta Engineering Blog to learn more about what our team is working on! What you’ll do as an engineer working on Applied AI at Vanta: Work cross-functionally to design and implement AI-powered features to deliver customer value and integrate LLMs with Vanta’s existing products and systems. You’ll work with other product engineers across Vanta to understand how AI systems can accelerate product adoption at Vanta Instrument evaluations, guardrails, and monitoring, and review customer usage to continually improve quality Collaborate with AI Platform engineers shaping foundational AI systems and tooling that accelerate product teams Make pragmatic tradeoffs that consider business priorities, user experience, and a sustainable technical foundation Mentor engineers, champion good technical and product instincts, and model a collaborative, high-ownership engineering culture How to be successful in this role: At least 7 years of industry experience as a software

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 As a Staff Machine Learning Engineer on Sentry’s AI/ML team, you’ll be directly responsible for developing the models and agents used to make our product smarter and more capable. This role is crucial; you will be at the forefront of integrating AI and machine learning into our core products, from issue triage and resolution to predictive analytics for application performance monitoring. Your work will help companies around the globe gain actionable insights into their software, enabling them to build better products, faster. In this role you will Build state-of-the-art agentic AI systems to triage, debug, and solve real production issues Leverage Sentry’s novel (and massive) dataset of errors, spans, and profiles Own the development of major initiatives in the AI/ML space You'll love this job if you Are driven by impact and enjoy working on high-stakes, high-visibility projects Enjoy building things. You will have the opportunity to join the AI/ML team as one of its foundational members Thrive in cross-functional teams and enjoy building features alongside developers and product teams Qualifications Minimum 4+ years of professional experience with a MS/PhD degree in computer science, machine learning, or a related field Minimum 6+ years of professional experience with Bachelor’s degree in computer science, machine learning, or a related field Demonstrated expertise building production-grade agentic systems and tools You are comfortable writing production quality code (we use Python) Expertise with deep learning frameworks (we use PyTorch) Familiarity in deploying machine learning models at scale in production