About the Team Enterprise Verticals builds role-specific ChatGPT Work experiences for high-value enterprise workflows. We combine product engineering, plugins and skills, connectors, data, evaluations, and customer evidence to turn useful demos into reliable daily work. This opening sits within the Technology vertical inside Enterprise Verticals. The group focuses on repeatable workflows for people at technology companies, beginning with functions such as data and analytics, sales, and design, and carries the shared platform needs—tool integration, permissions, quality measurement, and safe rollout—across those experiences. We work closely with Design, Research, GTM, Security, and platform teams, as well as with customers and design partners. Success means that people can reach a trustworthy first result, understand what the system did, and keep using the workflow—not merely that a prototype exists. About the Role We are looking for a full-stack product engineer who can own ambiguous enterprise workflows end to end: understand a customer problem, shape the product, build across frontend and backend, work through platform dependencies, instrument quality, and learn quickly with design partners. You will build across ChatGPT Work surfaces, services, plugins, connectors, and data or permission boundaries when the experience requires it. You will make quality and rollout observable through evaluations, product and operational signals, and clear fallback or rollback paths. This is a product-engineering role for someone who can move between user problems and system details without losing ownership of either. The strongest candidates will be able to turn specific customer evidence into a generalizable product, explain scope and architecture tradeoffs, and carry a feature from an early prototype through a bounded production rollout. In this role, you will: Build and ship role-specific workflows across ChatGPT Work surfaces, services, plugins, and connectors. Turn customer a
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Data Centers And Powered Land Sourcing Lead in United States
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About the Team The Recursive Self-Improvement (RSI) team works across research, engineering, product, and infrastructure to build AI systems that accelerate and ultimately conduct high-quality research at OpenAI. We work to automate real research workflows and improve research productivity by building systems and feedback loops, designing evaluations, and training models to develop missing capabilities. Our work spans the full lifecycle of model training, evaluation, and deployment to help researchers move faster and tackle increasingly ambitious problems. About the Role We’re hiring research scientists , research engineers , and AI systems engineers to work on automating research at OpenAI. This role is based in San Francisco, CA. In this role, you will: Design evaluations for research judgment, hypothesis generation and testing, and long-horizon experiment execution. Turn real research workflows and model failures into data and evaluation flywheels. Improve model research capabilities through agent harnesses, synthetic data, RL environments, and model training. Build and maintain safe, reliable integrations between our models and OpenAI’s research infrastructure. Develop research agents, experiment-orchestration systems, and sandboxed runtimes that support real research workflows. Create metrics and economic models to understand RSI’s current and future effects on research productivity, model capabilities, and the safety of internal deployments. This is a high-ownership role for researchers and engineers who thrive in ambiguity, move fluidly between research and implementation, and turn emerging opportunities into rigorous, reliable, scalable results. You might thrive in this role if you: Have research or engineering experience across LLM training, model evaluations, agent systems, synthetic data, research infrastructure, or large-scale distributed systems. Are a strong generalist who can move between open-ended research and practical implementation, turning ambig
About the Team The OpenAI Audit Team is on a mission to build the future of internal audit from the ground up. Our ambition will be powered by a high-energy, technically exceptional team with the judgment, intellectual curiosity, and creativity to harness the latest advances in AI and design a truly next-generation audit function. As AI reshapes how work is performed across the enterprise, Internal Audit will use AI, automation, and data analytics to identify and assess the most significant and emerging risks across the business, including technology, cybersecurity, finance, compliance, operations, and data. We will build trusted partnerships at every level—from the Board of Directors and senior leadership to the teams delivering on OpenAI’s mission every day. We will operate as both an independent assurance provider and a trusted advisor, bringing an objective and pragmatic perspective to critical decisions. By engaging closely with management while preserving our independence, we will help the business innovate responsibly, move with confidence, and manage risk without creating unnecessary barriers. About the Role As the Cybersecurity & Technology Audit Leader, you will help shape the strategy, methodology, technology, and culture of a new audit function. You will lead complex audits and advisory reviews of cybersecurity, technology, data, and AI-related risks while advising leaders on practical ways to strengthen governance, resilience, and risk management. You are an experienced, hands-on professional who combines deep technical expertise with strong business judgment. You can quickly move between executive-level governance questions and detailed technical analysis, use data to identify and assess risk, and form clear, well-supported conclusions in fast-moving or ambiguous situations. You will have meaningful influence over how the function develops, including how we apply AI, automation, and analytics to audit planning, testing, monitoring, and reporting. T
About the Team The Privacy Engineering team builds secure, reliable systems that help OpenAI meet its legal obligations while protecting user data. We partner closely with Legal and Engineering teams across OpenAI to support lawful data access requests and other critical legal workflows. Our work turns complex, high-stakes processes into auditable and dependable technical systems with clear human oversight and strong privacy and security controls. About the Role We’re looking for a full-stack Software Engineer to build the internal tools and data pipelines that power lawful data access request workflows and Legal Operations. You will work across product and data systems to make authorized retrieval and case handling accurate, efficient, and auditable. This role is well suited to someone who enjoys translating ambiguous operational requirements into durable systems, cares deeply about sensitive-data handling, and wants to improve both technical reliability and the day-to-day experience of the people operating these workflows. This role is based in San Francisco, CA, with two additional locations under consideration: London, UK, and Dublin, Ireland. 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, build, and operate backend systems and workflow tooling for the full lifecycle of lawful data access requests, from intake and scoping through authorized retrieval, review, preparation, and audit. Build reliable data pipelines and interfaces across products and data stores so authorized teams can locate and handle the right records accurately and reproducibly. Implement least-privilege access, approval gates, provenance, audit trails, data minimization, and safe failure modes for sensitive workflows. Partner with Legal and Legal Operations to translate legal and operational requirements into clear technical designs and intuitive operator experiences. Identify responsible automation o
About the Team OpenAI is building Procurement of the future: one that uses AI-enabled systems, clean data, and scalable processes to help the business absorb increasing complexity, speed, volume, and throughput while enabling teams across OpenAI to operate more strategically and at greater scale while managing risk responsibly. The Procurement Operations team supports the operational flow of purchasing across OpenAI, helping teams turn business needs into complete, policy-aligned, and executable procurement activity. We partner across Procurement, Finance, Legal, Security, Accounting, Accounts Payable, Systems, and business teams to improve how requests, suppliers, purchase orders, approvals, data, documentation, and downstream handoffs move through our systems. As OpenAI scales, we are building procurement operations that can absorb increasing complexity without adding unnecessary friction. That means using AI thoughtfully, simplifying where we can, strengthening operating discipline where we must, and continuously improving how our stakeholders experience procurement. About the Role We are hiring two Senior Managers, Procurement Operations to manage the operational backbone of how OpenAI turns requests into committed, controlled, and payable spend. One role will focus on Technology categories, and the other will focus on Corporate Services categories. These roles are not removed from the work. You will be expected to review requests in the system, make or guide request and PO updates, resolve operational issues, and use that firsthand view to identify what needs to change. You will push the envelope without losing the thread on risk, staying close enough to the details to understand where friction, ambiguity, and control gaps show up. You will help improve procurement outcomes across intake, purchase requests, PO quality, supplier coordination, approval workflows, documentation, service delivery, and downstream financial handoffs. You will oversee and improve oper
About the Team The Pricing & Monetization team is responsible for how our products create and capture value. We partner closely with Product, Engineering, Data Science, GTM, and Finance to design pricing models, packaging, and commercial strategies that support adoption, growth, and long-term scaling of the business. To thrive in this team, you need to be a proactive problem-solver who excels at bringing structure to ambiguous challenges. Our work demands strategic thinking, cross-functional collaboration, and precision in execution. Team members succeed when they are analytical, detail-oriented, skilled at balancing multiple priorities, and passionate about driving high-stakes projects forward to deliver meaningful results. About the Role We are looking for a Pricing Strategist to shape how we price and monetize OpenAI’s API platform. You’ll own the end-to-end pricing strategy across model launches, price architecture, packaging, commitments and discounts, and monetization guardrails. You’ll work closely with senior leaders across Product, Engineering, Data Science, GTM, and Finance to define pricing approaches, improve commercial decision-making, and bring more rigor to how we monetize our API offerings. You should be comfortable building monetization frameworks and commercial policies, analyzing tradeoffs, supporting high-impact decisions and driving decision making. You should also care deeply about the customer perspective and believe that strong pricing reflects a real understanding of customer value, needs, and friction points in order to build pricing that is clear, fair, and aligned with how customers experience our products. This role will report to the Head of Product Pricing for API & Platform. What you’ll do Develop the end-to-end pricing strategy for our API platform, including model launch pricing, price architecture, packaging, discount logic, and monetization guardrails. Recommend pricing for new models, capabilities, and platform offerings,
The ChatGPT Finances team builds experiences that help people connect their financial accounts, understand their financial picture, and ask useful questions about their finances through ChatGPT. Our work spans account connectivity, data ingestion, dashboards, personalized insights, and conversational experiences. We collaborate across product, design, research, infrastructure, security, and data integrations to make complex financial information understandable and actionable. This is an early and ambitious product area with a substantial roadmap. We are looking for engineers who want to shape both the first user experiences and the durable systems required to earn and keep users’ trust. About the role We’re looking for full-stack product engineers to build and scale ChatGPT Finances. You will own features across the stack—from polished frontend experiences to the APIs, services, and data models that power them. This role is well suited to engineers who combine strong product judgment with broad technical depth. You should care about how quickly users can understand their financial lives, how reliably data moves through the system, and how AI can answer financial questions in a grounded, transparent, and useful way. You will work closely with product, design, research, infrastructure, security, and data integration teams to take ideas from early prototypes to reliable production experiences. In this role, you will Own full-stack product features from user experience and frontend implementation through backend services, data models, deployment, and observability. Build polished, accessible, and performant interfaces for account connection, dashboards, insights, and conversational workflows. Design APIs and backend systems that safely ingest, normalize, and serve financial data. Build resilient integrations that handle synchronization, data freshness, partial failures, permissions, and user consent. Bring new AI capabilities into production while prioritizing grounding
About the Team OpenAI is building Procurement of the future: one that uses AI-enabled systems, clean data, and scalable processes to help the business absorb increasing complexity, speed, volume, and throughput — while enabling teams across OpenAI to operate more strategically and at greater scale. The Hardware Procurement Operations team supports the operational flow of goods and hardware purchasing across OpenAI's hardware business units. We help teams turn business needs into controlled, accurate, and executable procurement activity, from request intake through purchase orders, supplier coordination, change management, receiving readiness, and downstream invoice support. As OpenAI scales, we are building procurement operations that can support changing hardware needs, new business unit priorities, and increasing operational complexity. That means creating practical standards where they help, preserving flexibility where the business requires it, and continuously improving how requests, suppliers, POs, data, and controls move through our systems. About the Role As a Senior Manager of Procurement Operations focused on Hardware, you will own procurement operations for one or more assigned hardware business units. You will be the day-to-day DRI for hardware and goods procurement activity, leading work from intake through purchase requests, POs, supplier needs, changes, receiving readiness, and operational escalations. This is a hands-on operator-builder role for someone who understands the practical complexity of hardware and goods procurement and can both run the work and redesign how the work gets done. You will keep work moving while improving the operating model through better systems, workflows, automation, AI-enabled processes, controls, metrics, and operating leverage. You will evaluate how people, process, policy, systems, data, fiscal controls, and accounting practices come together, and you will work closely with other Central Procurement and BU Procurement
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 Equity Administration at OpenAI is responsible for the operational foundation of our equity programs. Our team ensures equity data and reporting are reliable, our systems and integrations are resilient, and our processes and controls are built to scale globally. We work cross-functionally with Legal, Finance/Accounting, Payroll, Tax, People, and key vendors to uphold compliance requirements and enable equity strategy as the company evolves. About the Role We’re looking for an experienced Manager, Global Equity Administration to help run our global equity programs with a focus on high-quality execution, scalable processes, auditable controls, and reliable equity systems. You will be hands-on in day-to-day equity administration and help improve how we operate as we scale. You will report to the Head of Equity Administration and partner closely with Legal, Equity Programs, Compensation, Tax, Payroll, and Finance to ensure equity operations are accurate, timely, and employee-friendly. Location: 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: Execute end-to-end employee equity administration across key lifecycle events (new grants, vesting/RSU releases, option exercises, and related transactions). Run recurring operational cycles by managing timelines, checklists, stakeholder inputs, and issue resolution. Produce audit-ready equity reporting and support accounting, compliance, and reporting needs with accurate, well-documented data. Build and maintain automated reporting (scheduled reports, dashboards, reconciliations) to reduce manual effort and improve speed and accuracy. Support equity system operations (Shareworks or comparable) including troubleshooting, configuration updates, permissions, report builds, and workflow maintenance. Partner with Internal Controls to keep process documentation, narratives, and flowcharts current,
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 researcher focused on our embedding retrieval efforts. You’ll work with a a team of world-class research scientists and engineers developing foundational technology that enables models to retrieve and condition on the right information, at the right time. This includes designing new embedding training objectives, scalable vector store architectures, and dynamic indexing methods. This work will support retrieval across many OpenAI products and internal research efforts, with opportunities for scientific publication and deep technical impact. 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. Responsibilities Tackle embedding models and retrieval systems optimized for grounding, relevance, and adaptive reasoning. Collaborate with a team of researchers and engineers building end-to-end infrastructure for training, evaluati
About the Team The Privacy Engineering Team at OpenAI is committed to integrating privacy as a foundational element in OpenAI's mission of advancing Artificial General Intelligence (AGI). Our focus is on all OpenAI products and systems handling user data, striving to uphold the highest standards of data privacy and security. We build essential production services, develop novel privacy-preserving techniques, and equip cross-functional engineering and research partners with the necessary tools to ensure responsible data use. Our approach to prioritizing responsible data use is integral to OpenAI's mission of safely introducing AGI that offers widespread benefits. About the Role As a part of the Privacy Engineering Team, you will work on the frontlines of safeguarding user data while ensuring the usability and efficiency of our AI systems. You will help us understand and implement the latest research in privacy-enhancing technologies such as differential privacy, federated learning, and data memorization. Moreover, you will focus on investigating the interaction between privacy and machine learning, developing innovative techniques to improve data anonymization, and preventing model inversion and membership inference attacks. This position is located in San Francisco. Relocation assistance is available. In this role, you will: Design and prototype privacy-preserving machine-learning algorithms (e.g., differential privacy, secure aggregation, federated learning) that can be deployed at OpenAI scale. Measure and strengthen model robustness against privacy attacks such as membership inference, model inversion, and data memorization leaks—balancing utility with provable guarantees. Develop internal libraries, evaluation suites, and documentation that make cutting-edge privacy techniques accessible to engineering and research teams. Lead deep-dive investigations into the privacy–performance trade-offs of large models, publishing insights that inform model-training and prod
About the Team OpenAI’s Platform and Infrastructure Engineering organization advances the mission of deploying artificial general intelligence (AGI) for the benefit of all by delivering secure, scalable, and resilient technology solutions. Our team builds and maintains robust infrastructure that safeguards OpenAI’s data and systems while ensuring employees are well-equipped and seamlessly connected. By prioritizing security, reliability, and user-centric solutions, we empower OpenAI employees to drive impactful AI research, corporate operations, and product innovation. About the Role As a Software Engineer: Internal Applications, Enterprise, you will build internal products that make technology support and administration safer, faster, and less dependent on manual intervention. You will help reduce reliance on broadly privileged human actions, turn recurring technology problems into paved paths, and build agentic systems that can help resolve tickets end to end. A core part of the role is building the interfaces that bring employees, AI agents, and human responders together in a shared ITSM experience, with the right context, controls, and handoffs at each step. We are seeking engineers who enjoy working across frontend and backend layers on ambiguous, high-leverage enterprise problems. You should bring strong product judgment, solid backend engineering fundamentals, and an interest in building software that changes how technology support, system administration, and agent-assisted operations are delivered. The best fit will care as much about the quality of the operator and employee experience as the correctness of the backend systems behind it. In this role, you will: Build frontend experiences that let employees request help, let agents gather context and take safe actions, and let human responders review, approve, or take over without losing the thread. Reduce reliance on broadly privileged manual actions by replacing them with narrow, auditable, policy-aware aut
About the Team: The OpenAI API team builds the foundation that enables every developer to harness OpenAI’s models safely, reliably, and at scale. We design and operate the systems that power model serving, API access, billing, developer tooling, and enterprise integrations—forming the connective tissue between OpenAI’s research breakthroughs and real-world products. Our mission is to make it effortless for anyone to build with OpenAI technology. We’re responsible for the infrastructure and product layers that allow millions of developers to integrate GPT models, fine-tune behavior, manage data, and deliver transformative experiences to their users. We collaborate across product, research, and engineering teams to ensure that innovation in model capabilities translates directly into value for customers. The API team spans multiple disciplines, including product management, infrastructure engineering, developer experience, and data systems. We care deeply about reliability, scalability, and simplicity—creating tools that let developers focus on their ideas while we handle the complexity of running world-class AI systems. About the Role: We are seeking an experienced Product Manager to define and scale the construction of our data processing, data privacy, billing, and access controls products. You will set strategy and execute on projects like expanding our regional data processing footprint, enabling new inference caching controls in the API or building APIs that make it easier for organizations to manage their spend limits. You will also define the strategy and ship foundational capabilities that ensure customers use OpenAI products securely, privately, and with enterprise-grade controls. This role partners deeply with engineering, security, legal, compliance, finance and leadership to deliver high-trust, enterprise-grade systems. 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 n
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
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