It Operations Analyst Jobs

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We embed deeply with users to solve high-leverage problems. We move quickly from prototype to deployment and surface patterns that shape the platform. We operate at the intersection of customer delivery and core development. We work closely with Product, Research, and Go-To-Market (GTM). About the role Forward Deployed Engineers lead complex deployments of frontier models in production. You will embed with customers where model performance matters, delivery is urgent, and ambiguity is the default. You will use this to map their problems,You will use this to map their problems, structure delivery, and ship fast. You will scope, sequence, and build full-stack solutions that create measurable value. You will also drive clarity across internal and external teams. You will identify reusable patterns and share field signal that influences the roadmap. Success in this role means owning the delivery state across workstreams. You will hold the bar on quality and pace and help OpenAI learn through execution. This role is based in Abu Dhabi. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own technical delivery across multiple deployments from first prototype to stable production Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Scope work, sequence delivery, and remove blockers early Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks that others can use Share field feedback that helps Research and Product understand where the models succeed and where they c

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a researcher working on Frontier Evals & Environments, you will help build north star model environments to drive progress towards safe AGI/ASI. Your work will directly guide the research programs of the most ambitious training runs happening at OpenAI. Some prior open-sourced evaluations built by researchers in this role include GDPval , SWE-bench Verified , MLE-bench , PaperBench , and SWE-Lancer . If you are interested in feeling firsthand the fast progress of our models, and steering them towards good outcomes, this is the role for you. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. In this role, you might Create ambitious RL environments to push our models to their limits, and measure frontie

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team builds the data, environments, graders, training methods, and feedback loops that shape what OpenAI’s next agents can do and what they are like to work with, then carries those improvements through major training runs and into products used by people every day. About the Role As a member of the Agent Post-training Personality team, you will help make OpenAI’s agents exceptional collaborators. You will study what makes an agent thoughtful, clear, perceptive, appropriately proactive, and genuinely easy to work with, then translate those insights into evals, training data, reward signals, and model improvements. We use “personality” to mean much more than writing style or general likability. It includes whether an agent understands what the user is trying to accomplish, communicates with good judgment, adapts to context, asks useful questions, handles disagreement honestly and takes initiative at the right moments. The goal is to create a strong, tasteful default that can adapt to different people and situations. This work combines behavioral research, product thinking, research and communication taste. You will collaborate with product teams, human experts, and researchers across post-training and pretraining to ensure that improvements survive the full trai

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role We believe that the final enabler for AGI is spending compute on context. As a Context Researcher on Agent Post-Training, you will scale compute spent on context. You will get to work in our frontier training stack on enabling the next paradigm of model training with a clear product interface for iterative deployment (Codex Chronicle). You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. In this role, you might Design and run experiments that improve scaling of compute on context. Own end-to-end improvements to the post-training stack, including RL, data pipelines, graders, reward signals, evals, diagnostics, and model-behavior analysis. Build evals and environments that expose the next set of model failures,

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the role Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own technical delivery across multiple deployments from first prototype to stable production Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Scope work, sequence delivery, and remove blockers early Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks that others can use Share field feedback that helps Research and Product understand where the models succeed and where they can improve Keep teams moving through clarity and follow-through You might thrive in this role if you Bring 5+ years of engineering or technical deployment experience that includes customer-facing work Have scoped and delivered complex systems in fast-moving or ambiguous environments Write and review production-grade code across frontend and backend using Python, JavaScript,

About the Team Join the engineering teams that bring OpenAI’s ideas safely to the world! The Applied Engineering team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role We’re seeking Software Engineers who can solve complex, high-impact problems across our stack. In this role, you’ll join a nimble team driving the deployment of OpenAI’s technology into new environments and infrastructure that power critical missions in the public sector. You’ll work cross-functionally with product, security, and compliance teams to build the functionality needed to deliver a scalable, reliable platform. You’ll also partner directly with customers to design and build new products and features that create real-world impact. From launching net-new capabilities to optimizing how we serve inference in unique, high-stakes environments, this role offers both breadth and technical depth—giving you the opportunity to shape the future of OpenAI’s technology where it matters most. This role is based in Washington D.C., San Francisco, CA or Seattle, WA. Occasional travel to customer sites is required for this role. In this role, you will: Own the development of new customer-facing ChatGPT and OpenAI API features end-to-end, both on-premises and in the cloud, for our public sector customers. Partner and directly embed with teams across the business, including engineering, security, and compliance, to enable our products to work within the unique constraints of new environments. Talk to users to understand their problems and design solutions to address them Work with the research team to get relevant feedback and iterate on their latest models, developing solutions specific for public sector customers at both the model & data

About the Team OpenAI’s Applications Engineering organization builds and operates the products (such as ChatGPT & Codex) that bring our cutting-edge research to millions of users and developers worldwide. The Applied Foundations team owns the core product and platform layers that make those experiences possible — from identity & access, to safety to payments & commerce across all of our apps. Our teams span product engineering, infrastructure, and safety, working together to deliver technology that is reliable, secure, and trusted at global scale. About the Role We’re hiring Backend Software Engineers to design and implement safe services and infrastructure that power our core products. What You’ll Do Architect, build, and improve scalable backend systems and APIs. Drive performance, reliability, and safety across distributed services. Implement data storage, retrieval, compute, and integration solutions. Participate in long-term architectural planning and technical design reviews. Collaborate with cross-functional teams to design solutions that protect against and mitigate adversarial attacks without compromising user experience. You Might Thrive Here If You: Have strong experience with distributed systems, APIs, and backend languages (e.g., Go, Python, Rust, C++). Have experience setting up and maintaining production backend services and data pipelines. Have a humble attitude, an eagerness to help your colleagues, and a desire to do whatever it takes to make the team succeed. Enjoy building resilient services that handle large scale and complexity. Are self-directed and enjoy figuring out the best way to solve a particular problem Own problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the role Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. This role is based in NYC. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own technical delivery across multiple deployments from first prototype to stable production Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Scope work, sequence delivery, and remove blockers early Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks that others can use Share field feedback that helps Research and Product understand where the models succeed and where they can improve Keep teams moving through clarity and follow-through You might thrive in this role if you Bring 5+ years of engineering or technical deployment experience that includes customer-facing work Have scoped and delivered complex systems in fast-moving or ambiguous environments Write and review production-grade code across frontend and backend using Python, JavaScript, or compar

About the Team OpenAI’s Applications Engineering organization builds and operates the products (such as ChatGPT & Codex) that bring our cutting-edge research to millions of users and developers worldwide. The Applied Foundations team owns the core product and platform layers that make those experiences possible — from identity & access, to safety to payments & commerce across all of our apps. Our teams span product engineering, infrastructure, and safety, working together to deliver technology that is reliable, secure, and trusted at global scale. About the Role We’re hiring Full-Stack Software Engineers to design and implement safe services, systems and infrastructure that power our core products. In this role, you will: Architect, build, and improve frontend and backend systems. Work across the full stack to build products and systems from initial exploration through launch readiness. Participate in long-term architectural planning and technical design reviews. Collaborate with cross-functional teams to design solutions that protect against and mitigate adversarial attacks without compromising user experience. You might thrive in this role if you: Have built and shipped full-stack apps or systems end-to-end — in fast-moving, startup-like environments. Have a humble attitude, an eagerness to help your colleagues, and a desire to do whatever it takes to make the team succeed. Enjoy building resilient products and services that handle large scale and complexity. Are self-directed and enjoy figuring out the best way to solve a particular problem Own problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool t

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of Agent Post-Training, Computer Use, you will teach models to operate computers. You will help train models that can navigate browsers and desktops, use tools and applications, reason through complex workflows, collaborate with users and other agents, and complete long-horizon tasks with reliability and judgment. This work sits at the intersection of frontier model training, product behavior, evaluation, and systems engineering, and will directly shape the computer-use capabilities shipped in OpenAI’s next generation of agents. Currently, our models are the best in the world at this behavior! You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. In this role, you might Design and run experiments th

About the Team Safety Systems works to ensure OpenAI’s most capable models can be developed and deployed responsibly. Our work spans evaluations, safeguards, red teaming, deployment decisions, and the systems that help OpenAI understand and reduce risk as models become more capable and widely used. Within Safety Systems, the Trustworthy AI team is growing its safety transparency function: a practice focused on helping external audiences understand OpenAI’s technical safety work with greater clarity, rigor, and continuity. We create and improve the public artifacts that explain how our systems are evaluated for safety, what safeguards we build, what decisions we make, and where uncertainty remains. This work includes system cards, the Deployment Safety Hub, safety-related blogs, public governance documents, and other outputs that communicate technical safety topics to external audiences. It also includes building new ways to make technical safety information easier to understand, navigate, and use—including AI-assisted workflows, data visualizations, and interactive tools that make complex technical work more legible over time. About the Role We are looking for a Safety Transparency Editor to own the editorial quality of key safety transparency artifacts and systems. This is a hands-on role for someone who can write crystal-clear, pitch-perfect explanations of the hardest and highest-stakes technical safety topics that OpenAI tackles, and who can lean into AI to build systems that help the broader organization do this work better. Your core responsibility is to shape and execute how our technical safety work is externally communicated: identifying the narrative thread, exercising judgment about which details matter, determining where additional context, explanation, or supporting evidence is needed, translating complexity without sacrificing precision, and helping external audiences understand both the safety measures we’ve taken and the uncertainties that remain. To

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of Agent Post-Training, Artifacts, you will train frontier models to create polished, useful work products: documents, spreadsheets, slide decks, dashboards, reports, analyses, and other interactive or editable artifacts. You will help teach our models to move from a vague user goal to a finished artifact with strong structure, visual taste, domain judgment, correctness, and low latency. This work will require owning improvements across our post-training stack, including RL, data pipelines, graders, reward signals, evals, and behavioral analysis. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. In this role, you will: Design and run experiments that improve agentic model behavior for complex so

About the Team The RL and Reasoning team drives the core reasoning paradigm and has created groundbreaking innovations such as o1 and o3. They focus on pushing the boundaries of reinforcement learning research, building next-generation generative models, and deploying them at scale. About the Role As a Research Engineer/Research Scientist at OpenAI, you will advance the frontier of AI alignment and capabilities through cutting-edge RL methods. Your work will sit at the heart of training intelligent, aligned, and general-purpose agents, including the systems that power various models. We’re looking for people who have a background in reinforcement learning research, are able to iterate quickly, and are proficient at coding. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. You might thrive in this role if: You love being on the cutting edge of RL and language model research. You’re a self-starter who takes initiative and ownership of ideas, driving them to completion. You value principled approaches, simple experiments in tightly-controlled settings, and reaching trustworthy conclusions which stand the test of time. You thrive in a fast-paced, dynamic, and technically complex environment where rapid iteration is key. You’re comfortable diving into a large ML codebase to debug and improve it. You have a deep understanding of machine learning and machine learning applications. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the ful

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the role Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. This role is based in Tokyo. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. Travel is expected in this role, mainly within Japan. To succeed in this position you must be bilingual—fluent in both Japanese and English (spoken and written). Please note that your resume must be submitted in English, and the interview process will include conversations in both languages. In this role you will Own technical delivery across multiple deployments from first prototype to stable production Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Scope work, sequence delivery, and remove blockers early Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks that others can use Share field feedback that helps Research and Product understand where the models succeed and where they can improve Keep teams moving through clarity and follow-through You might thrive in this role if you Bri

About the Team We are building general-purpose robotics. In the short term, we are focused on robots to support skilled workers to build our future infrastructure. In the long term, we imagine everyone having a personal robot doing anything they need. Progress is rapid, and based on a foundation of co-design between robotics hardware and ML research. About the Role As a Firmware Engineer, you will define and drive the architecture of embedded systems for next-generation hardware products. You will own foundational firmware decisions across real-time execution, device bring-up, hardware interfaces, fault handling, safety mechanisms, and production readiness. We’re looking for someone with deep experience building safety-critical or high-consequence systems, where failures can have meaningful consequences. You should be comfortable reasoning about risk, designing for diagnosability and graceful degradation, and creating engineering practices that raise the reliability bar for the entire team. You should also be unusually good at moving fast. Sometimes the right answer is a carefully reviewed architecture that will endure for years; sometimes it is getting a rough-but-useful prototype working by the end of the afternoon so the team can learn something concrete tomorrow. We value engineers who know the difference, make that call well, and can operate credibly in both modes. You will be both a technical leader and a hands-on builder: setting direction, reviewing critical designs, unblocking the hardest problems, and writing production firmware when it matters most. Our embedded stack uses a lot of Rust. Extensive experience in the language is a big help! This role is based in San Francisco, CA. This role will be expected to be in office 4 days per week and offer relocation assistance to new employees. In this role, you will: Rapidly bring up new hardware and set execution pace for the team. Lead firmware architecture for embedded systems spanning boot, RTOS/runtime behav