Engineering Lead Analyst Jobs

About the team ​​Preparedness is a critical Safety Research team at OpenAI, which is focused on mitigating AI threats to global security that could scale to an extreme level of severity. Our work involves: Measurement. Monitoring and predicting the evolving capabilities of frontier AI systems. Mitigation. Keeping misuse safeguards, alignment tools, and security measures on track to adequately address extreme threats that might arise in the future. Coordination. Setting mitigation targets by maintaining OpenAI’s preparedness framework , and partnering with other staff to achieve these targets. This is urgent, fast-paced work that has far-reaching implications for the company and for society. About the role Models are becoming increasingly capable—moving from tools that assist humans to agents that can plan, execute, and adapt in the real world. As we push toward AGI, cybersecurity becomes one of the most important and urgent frontiers: the same systems that can accelerate productivity can also accelerate exploitation. As a Researcher for cybersecurity risks, you will help design and implement an end-to-end mitigation stack to reduce severe cyber misuse across OpenAI’s products. This role requires strong technical depth and close cross-functional collaboration to ensure safeguards are enforceable, scalable, and effective. You’ll contribute directly to building protections that remain robust as products, model capabilities, and attacker behaviors evolve. In this role, you will: Design and implement mitigation components for model-enabled cybersecurity misuse—spanning prevention, monitoring, detection, and enforcement—under the guidance of senior technical and risk leadership. Integrate safeguards across product surfaces in partnership with product and engineering teams, helping ensure protections are consistent, low-latency, and scale with usage and new model capabilities. Evaluate technical trade-offs within the cybersecurity risk domain (coverage, latency, model util

About the Team OpenAI’s API Platform organization builds the products and infrastructure that help first-party and third-party developers build with OpenAI models. We ship the API primitives, tools, SDKs, documentation, playgrounds, and platform experiences that make OpenAI’s capabilities reliable, understandable, and useful in production. The API Experience team is focused on the end-to-end developer experience for the OpenAI API. We own the surfaces developers touch every day: docs, SDKs, the Playground, examples, onboarding flows, and the systems that help developers go from first request to production deployment quickly and confidently. About the Role We’re looking for full stack and frontend engineers to help define and build the next generation of OpenAI’s developer experience. In this role, you’ll work across frontend product surfaces, backend systems, SDK and documentation pipelines, and API workflows that serve millions of developers and companies. You’ll partner closely with product, design, research, API engineering, and developer-facing teams to make complex AI capabilities simple to understand, easy to test, and safe to launch in real-world applications. This is a highly cross-functional role for someone who cares deeply about craft, developer empathy, reliability, and product velocity. In this role, you will: Build and scale developer-facing products including the OpenAI API Playground, documentation experiences, onboarding flows, examples, and API workflow tools. Own full stack projects end to end, from product definition and UX collaboration through backend implementation, launch, measurement, and iteration. Improve the systems that generate, maintain, and publish SDKs, API references, docs, guides, and developer examples. Partner with API, research, design, and infrastructure teams to bring new model capabilities and API primitives to developers in a clear, usable way. Use developer feedback, product analytics, and direct customer insight to identif

About the team OpenAI’s mission is to build safe artificial general intelligence (AGI) which benefits all of humanity. This long-term undertaking brings the world’s best scientists, engineers, and business professionals into one lab together to accomplish this. In pursuit of this mission, our Go To Market (GTM) team is responsible for helping customers learn how to leverage and deploy our highly capable AI products across their business. The team is made of Sales, Solutions, Support, Marketing, and Partnership professionals that work together to create valuable solutions that will help bring AI to as many users as possible. About the role This role is part of our ANZ Mid-Market team which will own both named account pursuits and executing programmatic sales via OpenAI partners. You’ll be a key driver of writing the playbook for Mid-Market in APAC as an AI Native Sales team. You’ll work with researchers, engineers, and solution strategists to help customers evolve their industry with AI. This role is based in Sydney. In this role, you'll: Manage a portfolio of accounts, developing and executing strategies for a comprehensive regional go to market plan Win lighthouse accounts through outbound sales outreach Partner with solutions and research engineering to build and execute complex customer programs and projects Own a consumption revenue target Manage consumption revenue forecasts Support the recruitment and onboarding of other teammates Support the development of company culture We're seeking someone with experience including: 7+ years of direct selling experience in Data and AI or Cloud Designing and executing complex go to market strategies Orchestrating programmatic sales motions with partners Experience operating in fast paced, high growth environments Working directly with c-level executives Leading high-visibility customer events (CAB, conferences, product launches, etc.) Hands on experience with AI tools You might thrive in this role if you: Are customer-cent

About the Team The ChatGPT organization at OpenAI supports our mission by bringing advanced AI capabilities to hundreds of millions of users worldwide. The Image Generation team is responsible for one of the fastest-growing experiences in ChatGPT, enabling users to create, edit, and transform images through natural language. Recent breakthroughs in multimodal AI have dramatically improved image quality, instruction following, editing precision, consistency, and text rendering. We're building the systems and experiences that turn these research advances into products used daily by creators, professionals, businesses, and consumers around the world. Our team sits at the intersection of research, product, design, and infrastructure. We work closely with model researchers, mobile engineers, frontend engineers, and platform teams to build intuitive experiences and scalable systems that power image generation at global scale. Whether users are creating marketing assets, visualizing ideas, editing photos, designing products, or simply exploring their creativity, our goal is to make visual creation feel as natural as having a conversation. About the Role We are looking for an experienced Full Stack Engineer to join the Image Generation team and help shape the future of AI-powered visual creation. In this role, you'll own features end-to-end across both frontend and backend systems, building the experiences that enable users to generate, edit, organize, and interact with images inside ChatGPT. You'll work across the entire stack—from highly interactive user interfaces and real-time workflows to backend services, APIs, orchestration systems, and data infrastructure. This role is ideal for engineers who enjoy moving fluidly between product development and systems engineering, collaborating closely with design, product, and research teams to rapidly bring new AI capabilities to users. You'll help define entirely new interaction paradigms as multimodal AI continues to evolve. In

About the Team OpenAI, in close collaboration with our capital partners, is building the world's most advanced AI infrastructure ecosystem. The Scaling Analytics team serves as the data backbone for this effort, enabling leaders and operators to make informed decisions across infrastructure deployment, hardware operations, supply chain, capacity planning, and site execution. As OpenAI’s Industrial Compute expands across an increasing number of global data center campuses, the complexity of managing infrastructure capacity, hardware health, supply flows, and operational performance continues to grow. Scaling Analytics develops the data models, pipelines, metrics, and reporting systems that transform fragmented operational data into actionable insights, helping OpenAI operate infrastructure at unprecedented scale. About the Role We are seeking a Data Engineer to help build and scale the analytical foundations that power OpenAI's infrastructure organization. This individual will partner closely with Hardware Operations, Capacity Planning, Supply Chain, Infrastructure Delivery, Finance, and Engineering teams to create reliable data products that support critical operational and strategic decisions. Today, much of the team's expertise is concentrated within several highly specialized domains including hardware health, GPU attribution, and supply analytics. As Stargate grows and new sites come online, the demand for analytics support continues to expand across both existing and emerging problem spaces. This role will increase the team's ability to move quickly, reduce operational bottlenecks, and provide additional depth across critical infrastructure analytics functions. The ideal candidate combines strong data engineering fundamentals with an ability to navigate ambiguous operational environments, translating complex infrastructure problems into scalable data solutions that improve visibility, decision-making, and execution. Key Responsibilities Design, build, and maint

About the Team The Cloud Agents team builds product infrastructure for long-running agents in the cloud: orchestration, sandboxing and isolation, secure environment connectivity, secrets and identity, observability, reliability, and cost controls. These agents securely connect to diverse developer and customer environments and use tools to accomplish goals. We partner closely with product, research, and infrastructure teams to turn agentic capabilities into dependable platforms for OpenAI products and developers building on OpenAI. About the Role We are looking for an experienced software engineer to help build and scale our cloud agent platform. You will design and operate systems for orchestrating agents at scale. You will work closely with product engineers on ChatGPT, API, and Codex to define the right abstractions and enable them to ship products quickly. Strong backend or infrastructure experience is important; experience with Python, Rust, distributed systems, cloud infrastructure, or product platforms is especially helpful. In this role, you will: Design and scale the orchestration, sandboxing and storage systems that run agentic workloads for Codex, ChatGPT, and the OpenAI API. Partner with product engineers to build a platform that enables them to ship quickly and turn feedback into robust abstractions. Improve reliability, security, performance, and cost efficiency for long-running agents. Deploy services that can operate across different environments and clouds. Your background might look something like: 9+ years of professional engineering experience, excluding internships, in relevant roles at technology and product-driven companies. Experience leading large-scale backend, platform, or infrastructure projects from ambiguous problem statements to production systems. Proficiency in one or more backend languages such as Python, Go, Rust, TypeScript, or similar, and the ability to move across service, platform, and product boundaries. Strong understanding

About the team OpenAI’s mission is to build safe artificial general intelligence (AGI) which benefits all of humanity. This long-term undertaking brings the world’s best scientists, engineers, and business professionals into one lab together to accomplish this. In pursuit of this mission, our Go To Market (GTM) team is responsible for helping customers learn how to leverage and deploy our highly capable AI products across their business. The team is made of Sales, Solutions, Support, Marketing, and Partnership professionals that work together to create valuable solutions that will help bring AI to as many users as possible. About the role This role is part of our APAC Mid-Market team which will own both named account pursuits and executing programmatic sales via OpenAI partners. You’ll be a key driver of writing the playbook for Mid-Market in APAC as an AI Native Sales team. You’ll work with researchers, engineers, and solution strategists to help customers evolve their industry with AI. This role is based in Singapore. In this role, you'll: Manage a portfolio of accounts, developing and executing strategies for a comprehensive regional go to market plan. Win lighthouse accounts through outbound sales outreach. Partner with solutions and research engineering to build and execute complex customer programs and projects. Own a consumption revenue target. Manage consumption revenue forecasts. Support the recruitment and onboarding of other teammates. Support the development of company culture. We're seeking someone with experience including: 7+ years of direct selling experience in Data and AI or Cloud. Designing and executing complex go to market strategies. Orchestrating programmatic sales motions with partners. Experience operating in fast paced, high growth environments. Working directly with c-level executives. Leading high-visibility customer events (CAB, conferences, product launches, etc.). Hands on experience with AI tools. You might thrive in this role if you:

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, you will improve the capabilities, reliability, and product fit of OpenAI's agentic models. You might own a research direction, build the infrastructure that makes large training runs faster and more trustworthy, create evals that reveal where models fail, or drive a capability from an idea through experimentation, integration, and launch. This role is intentionally broad. The strongest candidates are not defined by one method or subfield; they are people who can take an ambiguous capability problem and make progress across research, engineering, data, evals, and product. You should be excited to work on models that act in the world: writing and debugging code, using tools, calling functions, operating computers, collaborating with other agents, and completing valuable work on behalf of users. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, meas

About the team OpenAI’s mission is to build safe artificial general intelligence (AGI) which benefits all of humanity. This long-term undertaking brings the world’s best scientists, engineers, and business professionals into one lab together to accomplish this. In pursuit of this mission, our Go To Market (GTM) team is responsible for helping customers learn how to leverage and deploy our highly capable AI products across their business. The team is made of Sales, Solutions, Support, Marketing, and Partnership professionals that work together to create valuable solutions that will help bring AI to as many users as possible. About the role Our Sales team has a unique mission to help customers understand the deep impact that highly capable AI models can bring to their business and clients. As an Account Director focused on Professional Services, you will partner with leading global consulting firms, systems integrators, IT services providers, and business process outsourcing organizations to help them transform how they deliver services, increase workforce productivity, accelerate software development, and build AI-powered offerings for their clients. This role is a mixture of technical understanding, executive engagement, strategic partnership, and value-driven selling. You'll work closely with customer executives to identify high-impact AI opportunities across consulting, delivery, engineering, operations, and managed services while collaborating internally with researchers, engineers, and solution strategists to bring these capabilities to market. You’ll be a key driver of opportunities through the entire sales cycle, from pipeline generation to closure, helping some of the world's largest professional services organizations reimagine how work is delivered with AI. 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. We are open to US-based remote candidat

About the Team OpenAI’s Safety teams work to ensure our products are safe, trusted, and resilient as frontier AI systems scale globally. We tackle some of the company’s most important challenges across understanding and preventing misuse and misalignment, intercepting fraud and abuse, and protecting vulnerable users. We are hiring Data Scientists to help build the analytical foundations that allow OpenAI to deploy increasingly capable AI responsibly. We are hiring Data Scientists across several teams that contribute to safety in different ways, including: Safety Systems Integrity Product Policy This is a high-impact role operating at the intersection of product, safety, policy, and research. About the Role As a Data Scientist, Safety, you will help solve complex and ambiguous problems where rigorous analysis directly informs critical decisions. Depending on your background and team alignment, you may work on areas such as: Measure harmful or abusive behavior across OpenAI’s products Detect fraud, manipulation, coordinated misuse Evaluate and improve safety classifiers, rules systems, mitigation systems, and human review workflows Design experiments and causal analyses to understand product, policy, and mitigation impacts Build prevalence estimators, dashboards, monitoring systems, and executive decision frameworks Diagnose gaps in safety and integrity systems using behavioral and product data, and help quantify and navigate false positive / false negative tradeoffs Translate ambiguous safety risks into measurable problems and evidence-based recommendations Partner with Product, Engineering, Policy, Research, and Operations teams to improve safety outcomes Build zero-to-one analytical systems in rapidly evolving domains Ideal Candidate We’re looking for strong Data Scientists who thrive in ambiguous, high-leverage environments. You may be a fit if you have: Strong statistical reasoning and analytical judgment Experience with experimentation, causal inference, or obse

The Fleet team at OpenAI supports the computing environment that powers our cutting-edge research and product development. We oversee large-scale systems that span data centers, GPUs, networking, and more, ensuring high availability, performance, and efficiency. Our work enables OpenAI’s models to operate seamlessly at scale, supporting both internal research and external products like ChatGPT. We prioritize safety, reliability, and responsible AI deployment over unchecked growth. About the Role The Software Engineer, Operating Systems & Orchestration will focus on building systems to manage hardware, configurations, vendors, and the people interacting with our infrastructure. You will design and develop solutions that integrate individual nodes and servers into unified clusters, directly contributing to advancing AI research by streamlining the overall research user experience. 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. In this role, you will: Design and build systems to manage both cloud and bare-metal fleets at scale. Develop tools that integrate low-level hardware metrics with high-level job scheduling and cluster management algorithms. Leverage LLMs to coordinate vendor operations and optimize infrastructure workflows. Automate infrastructure processes, reducing repetitive toil and improving system reliability. Collaborate with hardware, infrastructure, and research teams to ensure seamless integration across the stack. Continuously improve tools, automation, processes, and documentation to enhance operational efficiency. You might thrive in this role if you: Have strong software engineering skills with experience in large-scale infrastructure environments. Possess broad knowledge of cluster-level systems (e.g., Kubernetes, CI/CD pipelines, Terraform, cloud providers). Have deep expertise in server-level systems (e.g., systems, containerization, Chef,

About the Team Business Systems / Enterprise Platform Technology builds the internal systems, data foundations, workflow infrastructure, and enterprise platforms that help OpenAI operate at scale. The EPT AI Pod builds AI-native internal apps, MCP connectors, multi-agent workflows, and reusable platform capabilities across Finance, People, and GTM. About the Role As an Enterprise Applied AI Engineer, you will build internal apps for enterprise operations and the shared platform components those apps run on. This includes MCP connectors, multi-agent orchestration, data architecture, evals, monitoring, auditability, and governance. We’re looking for a hands-on engineer who is strong in Python, system design, enterprise integrations, data architecture, and applied AI systems. You should be excited to turn ambiguous business workflows into reliable internal products and shared infrastructure. In this role, you will: • Build internal apps for enterprise operations across Finance, People, and GTM • Build MCP connectors and enterprise integrations with strong auth, permissions, idempotency, retries, and rate-limit handling • Design end-to-end multi-agent workflows with tool routing, human approvals, audit trails, and safe action boundaries • Design data architecture for operational AI systems, including ingestion, schemas, quality checks, lineage, and governance • Build evals, monitoring, metrics, and regression tests for agentic workflows • Create reusable infrastructure, patterns, and components that other enterprise teams can build on • Partner with system owners and business owners to turn messy enterprise workflows into reliable internal products You might thrive in this role if you: • Have strong Python engineering skills for backend services, MCP connectors, agent/tool workflows, eval harnesses, and data ingestion jobs • Have strong system design skills across shared infrastructure, app architecture, reliability, and scaling • Have experience building internal apps,

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 this API & power-users team, you will improve the capabilities, reliability, and product fit of OpenAI’s agentic models for power users and API developers. You might design evals from real developer workflows, build training environments around production-like tool use, turn qualitative model failures into training data, evals, or post-training interventions, or drive a behavior improvement from discovery through post-training, integration, and launch. This role is intentionally broad. The strongest candidates are comfortable turning ambiguous model behavior problems into concrete progress, whether that means improving tool use, planning, instruction following, recovery from mistakes, or how models behave in API-based workflows. You should be excited to work across research, engineering, data, evals, and product to make models better at acting in real workflows. You will work closely with researchers, engineers, API/product teams, Codex, infrastructure, and safety/align

About the Team The Technical Success team is responsible for ensuring developers and enterprises are successful in building scalable production applications with the OpenAI API platform. We guide and support customers to achieve maximum benefits, value, and adoption from deploying our highly-capable models. OpenAI's customers represent a range of diverse backgrounds and maturity, from early-stage startups to established global enterprises. About the Role We are looking for a technically savvy and business-minded AI Deployment Engineer to deeply partner with our most strategic and high-impact platform customers, guiding them through application ideation, development, delivery, and scale to accelerate and maximize the value of what they build with our platform. You will have the opportunity to work on the most novel and creative use cases being built on our API, serving as a critical partner for collecting and delivering high fidelity feedback to Product and Research teams. This role is based in Tokyo, Japan. 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: Deeply embed with our most strategic platform customers, serving as their technical thought partner in ideating and building novel applications on our API. Proactively provide guidance to our customers on how to maximize business impact from their applications, accelerating their time to value. Experiment and prototype solutions with and for your customers. Forge and manage relationships with our customers’ leadership and stakeholders to ensure their application’s successful deployment and scale. Contribute to our open-source developer and enterprise resources. Scale the AI Deployment Engineering function through sharing knowledge, codifying best practices, and publishing notebooks to our internal and external repositories. Validate, synthesize, and deliver high-signal feedback to the Product and Research teams. Use your expertise i

About the Team The Future of Computing Research team is an Applied Research team within the Consumer Devices group focused on developing new methods and models as we advance forward in our mission of building AGI that benefits all of humanity. As a Software Engineer on the Future of Computing Research team, you will work together with both the best ML researchers in the world and the greatest design talent of our generation to push the frontier of model capabilities. About the Role We are looking for a Software Engineer to join our team to build tools and services that enable AI research, evaluation, and data generation workflows. The best work in this role will start with an ambiguous design question and turn it into working research systems. You will work closely with researchers, designers, and engineers to build the evaluation systems, synthetic data generation pipelines, review tools, and supporting platform services. The goal is to make these workflows easier to create, run, and trust without requiring bespoke engineering support for each new design concept. You will help ensure that research artifacts have a clear lifecycle, runs are reproducible and observable, and results provide useful evidence for product and model-training decisions while the underlying systems remain reliable and reusable. This role is based in San Francisco, CA. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees. In this role, you will: Build web applications, APIs, data models, and backend services for AI research workflows. Build tools to author and manage evaluation tasks, rubrics, graders, suites, and rollout configurations, including workflows for publishing, versioning, auditing, and sharing research artifacts. Automate evaluation runs and generate useful reports for design, research, and engineering teams. Support synthetic data generation workflows for multimodal and conversational research, including tools that comb