Product Operations Analyst in United States

About the Team The ChatGPT Model Flywheel team unified goal is to transform model advancements into great ChatGPT user experiences through reliable serving, rapid experimentation, safe deployment, and continuous improvement. Team Focus Areas Model Experimentation: Enable rapid, safe model validation for ChatGPT and Codex products through experiment automation and lifecycle management. Model Deployment: Ensure safe, scalable deployment of model capabilities with robust rollout and operational tooling. Automate capacity management and incorporate platform-wide health monitors. Model Measurement: Build comprehensive evaluation and measurement systems for model quality, from user signals to launch scorecards. Improve end-to-end feedback loops for continual model improvement. Key Partnerships Collaborate cross-functionally with teams including Model Measurement DS, Research, Codex, Fleet, Inference, and API. In this role, you will: Elevate and consolidate ChatGPT’s harness, context management, and system prompt frameworks. Drive expansion and improvement of multi-tier model experiences. Support and scale self-serve experiment capabilities and automated guardrails. Lead model rollout automation, capacity management, and health monitoring. Shape end-to-end measurement systems (evals, grader signals, user feedback, etc.). You might thrive in this role if you have: Proven experience leading engineering teams in complex, cross-functional environments. Demonstrated success shipping production systems at scale (ideally for AI or large backend services). Deep understanding of model-driven product development, deployment lifecycle, and measurement tooling. Excellent communication and collaboration skills—experience interfacing directly with engineering, research, and product stakeholders. Prior involvement with large language models, distributed infrastructure, or experimentation platforms is a plus. Why Work With Us Tackle highly impactful technical challenges at the cutting edg

About the Team The Hardware Health and Observability team owns the end-to-end health lifecycle of OpenAI’s global compute fleet. Our mission is to maximize healthy, usable compute across accelerator vendors, generations, cloud providers, and regions through reliable health signals, automated remediation, and scalable operational tooling. We build the systems that observe, detect, remediate, and verify hardware issues across GPUs, CPUs, networking, and platform infrastructure, enabling frontier model training and inference workloads to run reliably at hyperscale. We are the last line of defense for the success of OAI’s production and research workloads. About the Role On the Hardware Health and Observability team, you’ll build critical infrastructure that keeps OpenAI’s largest compute clusters healthy and operational at scale. Even small numbers of unhealthy systems can impact large-scale training and inference workloads. This team focuses on minimizing downtime, improving fleet efficiency, and ensuring compute resources remain continuously available to researchers and product teams. Engineers on this team own problems end-to-end, from defining health signals and debugging failures to building automated remediation systems that operate across millions of GPUs globally. In this role, you will: Define and maintain health signals across GPUs, CPUs, networking, and platform infrastructure. Build and evolve health checks that detect, remediate, and verify failures at scale. Ensure critical health checks execute with minimal latency to maximize workload uptime. Investigate hardware failures and system-level issues across large-scale compute environments. Own node lifecycle workflows including drain, quarantine, repair, RMA, and return-to-service processes. Build automation and tooling that enables global cluster management with minimal manual intervention. Partner with workload, reliability, and provider teams to integrate health signals into training and inference system

About the Team The Integrity team at OpenAI is dedicated to ensuring that our cutting-edge technology is not only revolutionary, but also secure from a myriad of adversarial threats. We strive to maintain the integrity of our platforms as they scale. The Integrity team is at the front lines of defending against misuse in all its forms: content abuse, scaled attacks, and other actions that could undermine the user experience or harm our operational stability. About the Role As a Machine Learning Engineer in OpenAI's Integrity team, you will have the opportunity to work with some of the brightest minds in AI. You’ll work on state-of-the-art models and classifiers, experiment with new architecture and approaches, and push forward our abilities in content and user understanding. You’ll help turn research breakthroughs into tangible solutions that improve the trust and safety of our platform. If you're excited about training LLMs and building ML models, this role is your chance to make a significant mark. In this role, you will: Innovate and Deploy: Design and deploy advanced machine learning models that solve real-world problems. Bring OpenAI's research from concept to implementation, creating AI-driven applications with a direct impact. Collaborate with the Best: Work closely with researchers, software engineers, and product managers to understand complex business challenges and deliver AI-powered solutions. Be part of a dynamic team where ideas flow freely and creativity thrives. Optimize and Scale: Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready. Contribute to projects that require cutting-edge technology and innovative approaches. Learn and Lead: Stay ahead of the curve by engaging with the latest developments in machine learning and AI. Take part in code reviews, share knowledge, and lead by example to maintain high-quality engineering practices. Make a Difference: Monitor and maintain deployed m

About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Security team protects OpenAI’s technology, people, and products. We are technical in what we build but are operational in how we do our work, and are committed to supporting all products and research at OpenAI. Our Security team tenets include: prioritizing for impact, enabling researchers, preparing for future transformative technologies, and engaging a robust security culture. About the Role We’re seeking an exceptional Principal-level Offensive Security Engineer focused on deep, hands-on penetration testing of OpenAI’s agent-powered products, infrastructure, and model-integrated application surfaces. You’ll assess complex systems end to end, identify realistic vulnerabilities, validate exploitability and impact, and partner closely with engineering teams to drive durable fixes. This role will be primarily focused on continuously testing our agent-powered products like Codex and Operator. These systems are uniquely valuable targets because they’re rapidly evolving, can perform sensitive actions on behalf of users, and have large, diverse attack surfaces. You will play a crucial role in securing our agents by finding vulnerabilities that emerge from the interactions between the applications, infrastructure, tools, and models that power them. You’ll have the chance to not only find vulnerabilities, but actively drive their resolution, build reusable testing approaches, automate offensive security workflows with cutting-edge technologies, and use your attacker perspective to improve the security of OpenAI’s products. In this role you will: Conduct deep penetration tests of OpenAI’s agent-powered products, including web applications, APIs, cloud services, identity and authorization flows, CI/CD systems, and model-integrated product surfaces. Continuously hunt for exploitable vulnerabilities in the interactions between the appli

About OpenAI OpenAI is dedicated to ensuring that artificial general intelligence (AGI) benefits all of humanity. Our mission requires building not only world-class AI models, but also the infrastructure that enables those models to be deployed reliably, efficiently, and at global scale. As demand for AI continues to grow, we are expanding the ways OpenAI can bring high-performance inference capacity online across a diverse hardware ecosystem. About the Team The GPT Infrastructure team builds software that turns advanced inference and optimization research into production products. One focus is enabling strategic infrastructure partners and accelerator vendors to qualify and onboard new compute without a bespoke porting and optimization effort for every hardware platform. We build the control planes, APIs, secure partner-side execution environments, evaluation systems, artifact pipelines, and operational tooling that make these workflows repeatable and trustworthy. The work sits at the intersection of distributed systems, AI inference, compilers and runtimes, performance engineering, security, and external partnerships. About the Role We are seeking an experienced systems generalist who can work comfortably across the stack to help build an automated inference optimization platform. Given a workload, target hardware profile, compiler and runtime context, and a trusted verifier, the system runs durable optimization campaigns that generate, compile, execute, grade, and improve candidate kernels, runtime configurations, and serving-stack changes. You will design both the OpenAI-hosted control plane and the partner-side software that evaluates candidates on real accelerator hardware. The product must keep long-running workflows reliable, make performance results reproducible, and maintain clear trust boundaries around sensitive model and hardware information. This is a deeply cross-stack role, combining strong software engineering fundamentals with systems thinking and

About the Team The ChatGPT Learning team focuses on building the next generation of learning experiences inside ChatGPT. Learning is already one of the largest consumer use cases on the platform, with millions of people each week using ChatGPT to understand concepts, practice skills, and get unstuck while learning. Our goal is to evolve ChatGPT from a place people go for one-off answers into a platform that helps people learn, grow, and make progress over time. We are exploring how AI can expand access to powerful learning tools for people everywhere—helping individuals better understand the world, build new skills, and pursue their goals. This team sits at the intersection of product engineering, design, AI research, and education, working to bring powerful learning experiences to a global audience. About the Role As a Full Stack Engineer on the ChatGPT Learning team, you will help design and build new product experiences that enable millions of people to learn with ChatGPT. You’ll work across the stack—from user-facing interfaces to backend services—to ship product features that make learning more intuitive, engaging, and effective. You’ll collaborate closely with researchers and platform teams to bring cutting-edge model capabilities into real-world products, helping translate advances in AI into experiences that people can use every day. We’re looking for engineers who enjoy building polished product experiences, operating with high ownership, and solving ambiguous problems that sit at the intersection of AI research and consumer software. This role is based in San Francisco or New York City. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. What You’ll Do Build end-to-end product experiences that help people learn with ChatGPT. Design and implement new multimodal capabilities that bring text, images, voice, and interactive interfaces into learning workflows. Develop scalable backend services and APIs t

About the team OpenAI’s Forward Deployed Engineering (FDE) team turns research breakthroughs into production-grade systems. We embed deeply with customers to solve high-leverage problems and act as the delivery engine for our most complex large-scale engagements. We move quickly from prototype to production and surface reusable patterns that shape our platform. We operate at the intersection of deployment and development – working closely with OpenAI Research, Product and Partnerships. About the Role As a Technical Deployment Lead (TDL), you will define how OpenAI delivers complex systems to customers. You will own how they are built, shipped, and adopted. You’ll translate business outcomes into a technical plan, run day-to-day execution across FDEs, Researchers, and Customer Engineers, and partner with customer teams to ensure delivery supports their goals. You will own delivery end-to-end: embedding with customers to map workflows and success criteria, ensuring components ship on time, and leading readiness and change management for adoption. You’ll track progress, manage dependencies, make sequencing decisions, and drive 0→1 prototypes through MVP and scale. You will also share field insights with Product and Research to guide roadmap and priorities. Success will be measured first and foremost by impact - deployments that deliver measurable value against customer goals, drive adoption, and become critical to their workflows. Additional measures of success include delivery reliability (milestones hit, low reopen/churn), operating leverage (patterns reused across deployments), judgment under pressure, and product impact (field signal that shifts roadmaps/architectures). This is a high-trust, high-autonomy role. Success requires deep technical project management expertise, extreme ownership of outcomes, and an ability to immerse in customer workflows and partner with customer teams to solve complex engineering problems at pace. This role is based in San Francisco. W

About the Role We are seeking a Cloud Infrastructure Engineer to help design and evolve the platforms that power OpenAI’s products. In this role, you will be a hands-on technical leader, driving the architecture, scalability, reliability, and security of critical infrastructure systems. You will help define how we build and operate infrastructure at the next order of magnitude, while influencing technical direction across teams. This role is both deeply technical and highly strategic, requiring strong ownership, sound judgment, and the ability to partner effectively across engineering, product, and research organizations. In this role, you will: Design and build scalable, reliable, and secure infrastructure platforms that power OpenAI products Evolve cloud infrastructure abstractions that enable rapid product development across teams Architect systems to support significant growth, performance, and operational complexity Improve server orchestration, networking, distributed systems reliability, and infrastructure security posture Influence technical direction and infrastructure strategy across multiple teams Partner closely with product, research, and engineering teams to align infrastructure with evolving needs Own operational excellence, including participation in on-call rotations, incident response, and production readiness Mentor engineers and raise the overall technical bar of the organization Contribute to a culture of high ownership, low ego, and thoughtful collaboration You might thrive in this role if you: 8+ years of experience building and operating large-scale infrastructure systems Deep expertise in Kubernetes and container orchestration at scale Strong experience designing cloud abstractions and platform infrastructure (AWS, GCP, Azure, or similar) Proven track record of leading complex technical initiatives across teams Experience operating highly reliable, secure, and scalable distributed systems Security engineering experience or security backgroun

About the team OpenAI’s Forward Deployed Engineering (FDE) team turns research breakthroughs into production-grade systems. We embed deeply with customers to solve high-leverage problems and act as the delivery engine for our most complex large-scale engagements. We move quickly from prototype to production and surface reusable patterns that shape our platform. We operate at the intersection of deployment and development – working closely with OpenAI Research, Product and Partnerships. About the Role As a Technical Deployment Lead (TDL), you will define how OpenAI delivers complex systems to customers. You will own how they are built, shipped, and adopted. You’ll translate business outcomes into a technical plan, run day-to-day execution across FDEs, Researchers, and Customer Engineers, and partner with customer teams to ensure delivery supports their goals. You will own delivery end-to-end: embedding with customers to map workflows and success criteria, ensuring components ship on time, and leading readiness and change management for adoption. You’ll track progress, manage dependencies, make sequencing decisions, and drive 0→1 prototypes through MVP and scale. You will also share field insights with Product and Research to guide roadmap and priorities. Success will be measured first and foremost by impact - deployments that deliver measurable value against customer goals, drive adoption, and become critical to their workflows. Additional measures of success include delivery reliability (milestones hit, low reopen/churn), operating leverage (patterns reused across deployments), judgment under pressure, and product impact (field signal that shifts roadmaps/architectures). This is a high-trust, high-autonomy role. Success requires deep technical project management expertise, extreme ownership of outcomes, and an ability to immerse in customer workflows and partner with customer teams to solve complex engineering problems at pace. This role is based in NYC. We use a hy

About the Team OpenAI’s Stargate and 3P Engineering teams are responsible for building and scaling the external infrastructure ecosystem that powers advanced AI systems. We work across hyperscalers, colocation providers, cloud partners, and strategic third-party operators to turn contracted capacity into production-ready compute. Our scope spans the full lifecycle of external deployments: commercial alignment, technical readiness, network integration, hardware enablement, operational readiness, and long-range scaling strategy. As OpenAI’s infrastructure footprint expands globally, we need leaders who can convert complex partner environments into reliable, high-velocity capacity for training and inference workloads. About the Role We are seeking a Technical Program Manager, Token-as-a-Service (TaaS) to lead delivery of external compute capacity that directly serves OpenAI model workloads. In this role, you will own complex cross-functional programs that transform third-party infrastructure into usable tokens at scale. You will partner across engineering, capacity planning, networking, hardware, finance, product, and external providers to ensure that deployed capacity translates into real production throughput. This role sits at the intersection of infrastructure execution, systems readiness, and business impact. Success requires strong technical fluency, elite program management, and the ability to drive accountability across internal teams and external partners. This is a high-visibility role with direct impact on OpenAI’s ability to scale model training and inference globally. This role is based in San Francisco, CA, with a hybrid work model of 3 days in office per week. Relocation assistance is available. Key Responsibilities Lead end-to-end delivery programs that convert external infrastructure capacity into production-ready token supply. Own readiness across compute, storage, networking, security, and operational dependencies for third-party environments. Build

About the Team The Demo Studio is responsible for translating OpenAI’s most advanced capabilities into tangible, high-impact experiences for customers. We design and deliver the demos, applications, and environments that define how executives understand what is possible with AI. Our work sits at the intersection of product, engineering, design, and go-to-market. We operate as a hybrid of product studio and live production team, building experiences that are both technically credible and narratively compelling. About the Role We’re looking for a Demo Studio Lead to own the end-to-end demo experience for OpenAI’s major events, webinars, and strategic programs. This is a highly cross-functional role focused on translating cutting-edge AI capabilities into clear, compelling, and production-ready experiences. You will own the full demo portfolio for an event or initiative, spanning mainstage moments, breakout experiences, booths, and supporting content. You’ll define the narrative, architect workflows, build high-fidelity demo environments, direct presenters, and ensure flawless execution in live environments. This is not a traditional sales engineering, presentation, or narrowly scoped design role — it requires a combination of product thinking, technical fluency, storytelling, systems design, and operational excellence. A key part of the role is presenting the work directly: delivering live demonstrations to executive, technical, and industry audiences across mainstage, breakout, customer, and recorded settings. This role is ideal for someone who thrives in ambiguity, operates with strong ownership, and is excited about shaping how the world experiences AI firsthand. This is a hybrid role that can be based in either San Francisco or New York. In this role, you will: Own the end-to-end demo experience across OpenAI-hosted summits, webinars, third-party industry events, and strategic executive demonstrations. Translate approved product positioning, real OpenAI capabiliti

About the Team The Foundations Research team works on high-risk, high-reward ideas that could shape the next decade of AI. Our goal is to advance the science and data that enable our training and scaling efforts, with a particular focus on future frontier models. Pushing the boundaries of data, scaling laws, optimization techniques, model architectures, and efficiency improvements to propel our science. The Search team sits within Foundations, building agentic search by co-designing model–system interfaces with the core search stack (serving, indexing, retrieval) to translate model intent into reliable, real-world actions. Operating at the frontier of AI and information retrieval, the team develops large-scale systems that transform and index vast corpora, enabling models to reason over global knowledge and act dependably. In close partnership with researchers, we rapidly bring modeling breakthroughs into production and redefine how intelligent systems discover, retrieve, and synthesize information at planetary scale. About the Role We’re looking for a Software Engineer focused on building and scaling retrieval systems. You’ll work with a team of researchers and engineers to develop infrastructure that enables models to retrieve and act on the right information at the right time. This includes designing and operating indexing systems, retrieval pipelines, and serving layers. This work supports retrieval across OpenAI products and research, with direct impact on system performance, reliability, and scale. Responsibilities Build and scale retrieval infrastructure across indexing, serving, and query execution. Develop low-latency, high-throughput systems for real-time model interaction. Partner with research to productionize embedding and retrieval techniques. Support dense, sparse, and hybrid retrieval pipelines. Own system performance, reliability, and observability at scale. Collaborate across Pretraining, Inference, and Product teams to integrate retrieval end-to-e

About the Team The Integrity team at OpenAI is dedicated to ensuring that our cutting-edge technology is not only revolutionary, but also secure from a myriad of adversarial threats. We strive to maintain the integrity of our platforms as they scale. The Integrity team is at the front lines of defending against misuse in all its forms: content abuse, scaled attacks, and other actions that could undermine the user experience or harm our operational stability. About the Role As a Machine Learning Engineer in OpenAI's Integrity team, you will have the opportunity to work with some of the brightest minds in AI. You’ll work on state-of-the-art models and classifiers, experiment with new architecture and approaches, and push forward our abilities in content and user understanding. You’ll help turn research breakthroughs into tangible solutions that improve the trust and safety of our platform. If you're excited about training LLMs and building ML models, this role is your chance to make a significant mark. In this role, you will: Innovate and Deploy: Design and deploy advanced machine learning models that solve real-world problems. Bring OpenAI's research from concept to implementation, creating AI-driven applications with a direct impact. Collaborate with the Best: Work closely with researchers, software engineers, and product managers to understand complex business challenges and deliver AI-powered solutions. Be part of a dynamic team where ideas flow freely and creativity thrives. Optimize and Scale: Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready. Contribute to projects that require cutting-edge technology and innovative approaches. Learn and Lead: Stay ahead of the curve by engaging with the latest developments in machine learning and AI. Take part in code reviews, share knowledge, and lead by example to maintain high-quality engineering practices. Make a Difference: Monitor and maintain deployed m

Who Are We? Postman is the world’s leading API platform, used by more than 45 million+ developers and 500,000 organizations, including 98% of the Fortune 500. Postman is helping developers and professionals across the globe build the API-first world by simplifying each step of the API lifecycle and streamlining collaboration—enabling users to create better APIs, faster. The company is headquartered in San Francisco and has offices in Boston, New York, Austin, Tokyo, London, and Bangalore - where Postman was founded. Postman is privately held, with funding from Battery Ventures, BOND, Coatue, CRV, Insight Partners, and Nexus Venture Partners. Learn more at postman.com or connect with Postman on X via @getpostman. P.S: We highly recommend reading The "API-First World" graphic novel to understand the bigger picture and our vision at Postman. The Opportunity At Postman, we are revolutionizing the way developers build, trace, and automate API workflows with Postman Flows , a powerful visual programming tool designed to simplify the development and sharing of API-powered applications. With an intuitive drag-and-drop interface, Postman Flows enables teams to collaborate and showcase their APIs regardless of technical expertise. We are looking for a Software and Systems Engineer to help scale and maintain the Flows runtime system. This system runs mission-critical automations in the cloud, with a focus on low latency, high throughput, and high availability. You’ll play a vital role in developing, deploying, and operating our backend services and infrastructure in a Kubernetes-based cloud environment. We’re looking for an experienced engineer who is excited not only about hands-on building as we ship and iterate on a weekly basis to get our product ready for GA, but who can also serve as a role model and mentor to other engineers. This role involves making key technical decisions and improvements to the system, as well as effectively making impact through influence wit

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. We are hiring a talented Tech Lead Manager (TLM) to lead Snowflake’s System Under Test (SUT) team, responsible for evolving how Snowflake engineers test the Snowflake product locally and at scale in CI. The SUT empowers Snowflake engineers by delivering a reliable, low-latency and cost-efficient developer experience across a high-growth, high-demand surface area. As the TLM for SUT, you will lead a small and highly technical team at the intersection of CI, developer infrastructure, and product engineering. You will set direction, drive execution, and partner broadly across Engineering Systems and product teams to deliver a more reliable, faster, and more maintainable test platform for Snowflake’s engineers. In this role, you will: Lead, coach, and grow the SUT team while creating a high-energy, cohesive environment with strong planning, ownership, and career development. Own the roadmap and execution for SUT rollout across development environments, CI and AI workflows. Drive measurable improvements in startup reliability, latency, and cost, using clear SLOs, dashboards, and operational metrics to guide decisions and raise the bar on execution. Serve as the technical anchor for the SUT domain, shaping architecture and guiding the evolution from legacy systems to a composable