Executive Steward in San Francisco

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 Human Data Team creates custom data solutions driving groundbreaking research. Our work enhances and evaluates our flagship models and products like ChatGPT, GPT-5, and Sora, and contributes to safety initiatives through collaboration with our Preparedness and Safety Systems teams. About the Role As a Research Program Manager (RPM) in the Human Data team you will partner with research and engineering to design and implement pragmatic solutions for collecting high-quality data. You will be a key interface between our research roadmap, external vendors, AI trainers, and the Human Data engineering team. This role is based in our San Francisco HQ. In this role, you will: Collaborate with Research: Partner with researchers to scope data collection needs, define success metrics, and establish quality measurement frameworks. Design & Execute Data Collection Campaigns: Translate research needs into actionable plans and accelerate execution by leveraging existing tooling and iterating to reach the desired outcome. In many cases, you will need to implement scrappy new solutions while partnering with engineering to design robust/scalable solutions. Unblock Yourself: You must be deeply uncomfortable with the idea of sitting around waiting for external dependencies, and have the technical acumen and drive to figure out how to achieve at least partial success in the interim. Optimize Systems & Processes: Build and optimize dashboards to track campaign performance, leveraging SQL and Python for data analysis and actionable insights. Drive Technical Roadmaps: Collaborate with engineers to enhance data platforms, resolve blockers, and ensure security best practices such as access management. Scale Your Impact : Advise and empower program managers and vendors to drive day-to-day execution so that you can focus on addressing high priority opportunities. You might thrive in this role if you: Are proficient in SQL and Python for data analysis, including q

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role As a Supply Chain Program Manager, you will own material readiness and supply chain execution for critical hardware programs spanning custom silicon, systems, memory, storage, networking, and rack infrastructure. You will work cross-functionally with Engineering, Strategic Sourcing, Manufacturing Operations, Finance, Planning, Quality, and external suppliers to develop and execute scalable supply strategies that support aggressive product development and deployment timelines. This role requires deep understanding of hardware supply chains, material planning, NPI execution, supplier management, and operational scaling in constrained and rapidly evolving environments. In this role you will: Material Readiness & Supply Planning - Own end-to-end material readiness across NPI and production phases, including building the necessary framework and processes for enablement. Drive supply planning and execution for long lead-time and constrained commodities including ASICs, HBM, DDR, SSDs, networking, optics, power, thermal, and mechanicals. Build and manage material readiness plans aligned to proto/pre-EVT, EVT, DVT, PVT, and mass production schedules. Monitor supply health, lead times, inventory positions, allocation risk, and capacity constraints. Drive shortage management, allocation mitigation, and recovery planning. Coordinate supply commits, forecast alignment, and supply continuity planning with suppliers and manufacturing partners. Cross-Functional Program Ma

About the Team The Agent Infrastructure team at OpenAI is responsible for building systems that enable training and deployment of highly useful AI agents, both internally and for the world. We work hand-in-hand with researchers to design and scale the environment in which agentic models are trained – providing a workspace for AI models to execute code, debug issues, and develop software just as human SWEs do. Our training environment for agentic models operates at an extremely high scale and has the flexibility to emulate any environment in which an agent might work. At the same time, our team builds and maintains OpenAI’s core platform for the deployment and execution of agents in production. Our systems power products such as Codex, Operator, tool use in ChatGPT, and future agentic products. Some of the most challenging technical problems in scaling the capabilities and utility of agents and agentic models lie in the infrastructure layer – and our team is focused on building the research and production systems that enable OpenAI to train the most capable models in the world, and maximize the utility of our agentic products for users around the world. About the Role As a Software Engineer on the Agent Infrastructure team, you will have the opportunity to work closely with both research and product at OpenAI - building and scaling systems to train highly capable agentic models, and building the platform and integrations to launch new agents to hundreds of millions of users worldwide. Your work will consist of both building new capabilities - standing up the infrastructure and integrations needed to train more complex agentic models - and rapidly scaling these new capabilities to some of the largest compute clusters in the world. At the same time, you’ll be instrumental to the launch of agentic products at OpenAI - building, maintaining, and scaling the production platform on which all agents run. We’re looking for people with deep experience building AI infrastructu

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 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 OpenAI Finance is responsible for ensuring the organization is set up for success in pursuit of its mission. The Technical Accounting team plays a crucial role in helping OpenAI navigate complex, judgmental, and rapidly evolving accounting matters with rigor and clarity. We aim to bring both technical excellence and strong business partnership to some of the most novel accounting questions in the industry. About the Role As Senior Manager, Technical Accounting, Compute Infrastructure, you will lead the evaluation, documentation, and operationalization of complex accounting matters related to OpenAI's compute infrastructure, strategic investments, and other non-routine business activities.. This role sits at the intersection of U.S. GAAP technical accounting, infrastructure strategy, financial reporting, controls, and cross-functional execution. Key areas may include cloud compute arrangements, data center and colocation arrangements, lease accounting under ASC 842, power purchase agreements, strategic investments, consolidation evaluations under ASC 810, financial instruments, and other emerging or non-standard arrangements. This role is based in San Francisco, CA or remote. 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: Lead technical accounting analysis for complex, judgmental, and non-routine transactions under U.S. GAAP. Evaluate accounting implications for compute infrastructure arrangements, including cloud compute, data center, colocation, lease, PPA, infrastructure procurement, and related commercial arrangements. Partner with Controllership, Tax, Legal, FP&A, Procurement, Infrastructure, and other cross-functional teams to assess the accounting implications of new products, commercial arrangements, strategic transactions, and business initiatives. Prepare and review technical accounting memoranda, position papers, and other auditor-ready documentation.

About the Team OpenAI’s mission is to build safe artificial general intelligence (AGI) that benefits all of humanity. Achieving this requires bringing the world’s most exceptional talent under one roof to push the boundaries of what’s possible. Our Research Recruiting team plays a critical role in this effort. We are an embedded part of the research organization—working side by side with our research staff to deeply understand evolving priorities, build trust, and strategically shape the future of OpenAI’s talent. About the Role We are looking for a highly strategic recruiter to work closely with the Head of Research Recruiting on a small set of unusually important, high-touch searches and candidate relationships. This role will focus on exceptional talent who does not move through a standard recruiting process: highly visible researchers, technical leaders, operators, and other special-interest candidates where timing, discretion, market intelligence, and tailored engagement matter as much as process execution. This is not a conventional req-based recruiting role. You will help identify where the market is moving, develop intelligence on top talent and competitor activity, translate that intelligence into action, and orchestrate bespoke recruiting strategies for candidates who require a more nuanced path into OpenAI. You should be able to translate these signals and states into clear, actionable advice for leaders and then make it happen. In this role, you will: Partner directly with the Head of Research Recruiting and research leadership team to define priority talent targets and shape bespoke engagement strategies. Build and maintain deep market intelligence across frontier AI, research, engineering, and adjacent talent ecosystems, including competitor movement, candidate motivations, and relationship context. Proactively identify, map, and cultivate exceptional high-profile talent before there is a formal or standard hiring process attached. Translate weak signa

About the Team OpenAI Finance ensures the organization is positioned for long-term success as we pursue our mission. The Strategic Sourcing & Procurement function plays a critical role in enabling OpenAI to deliver impact across research, product development, technology infrastructure, and services by helping the company scale responsibly, securely, and with strong commercial discipline. Our work sits at the intersection of innovation and execution. We partner closely with teams across OpenAI to translate rapidly evolving business needs into scalable, compliant, and economically sound external partnerships. As OpenAI continues to grow at pace, services sourcing is becoming increasingly strategic across the company. Every business unit relies on external service providers in different ways — to extend capacity, access specialized expertise, support operations, and accelerate execution. Done well, Procurement becomes a source of trust and momentum, helping OpenAI move faster with the right partners, stronger commercial outcomes, and the right level of protection. About the Role We are seeking an experienced Strategic Sourcing (GTM) Leader to lead strategic sourcing and commercial enablement for OpenAI’s Go-to-Market organization across B2B and B2C channels. You will manage substantial and rapidly growing spend while shaping sourcing strategies and scalable commercial pathways across Media, Creative, Production, Influencer, Agency, Sponsorships, Analytics, Communications, and Event suppliers in support of high-impact global initiatives. You’ll help evolve our GTM procurement function from reactive deal support into a speed-enabling, scalable commercial engine that delivers cost efficiency, launch readiness, and strong governance in a fast-moving environment. In this role, you will: Develop and execute sourcing strategies across GTM, Brand, Global Affairs, Events, Growth, and Partnership activities—spanning both B2B and B2C channels—that align with our mission and b

About the Team The Corporate Development team sits at the intersection of OpenAI’s strategy and the global AI ecosystem. Partnering closely with research, engineering, product, GTM and business leaders, we analyze markets, technologies, and companies to identify opportunities that accelerate OpenAI’s mission and long-term strategy. Bringing together expertise in strategy, M&A, and integration, the team leads the end-to-end process of sourcing, evaluating, negotiating, and integrating acquisitions and other strategic transactions. About the Role This is a high-visibility, strategically critical, cross-functional role at the intersection of M&A execution, enterprise go-to-market, and operational excellence. You will lead the critical phase from diligence through integration planning and post-close follow-through, define repeatable integration playbooks, and partner directly with senior stakeholders to ensure each transaction delivers intended value. The ideal candidate brings structured, hands-on integration experience, with particular expertise in enterprise / B2B transactions and a passion for AI, including building an AI-native corp dev platform. This role is based in our San Francisco HQ. 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: Lead integration planning and strategic execution for acquisitions from diligence through post-close follow-through, with clear owners, milestones, risks, and decision points. Translate deal rationale into practical integration goals and plans across product, engineering, sales, partnerships, customer success, people, finance, legal, security, systems, and communications. Partner with deal leads during evaluation and diligence to assess integration considerations, including tech stack, talent assessment, GTM alignment, transaction structure, operational readiness, and execution risk. Advise sponsors on how best to bring onboard acquisitions

About the Team OpenAI's Research Data Team exists to accelerate the evaluation, safety and capabilities of our models and products. Made up of technical operators and software engineers, we design the methods in which we acquire and create data. About the Role As a Research Program Manager (RPM), Data Acquisition, you will partner with research, engineering, and operations to design and implement pragmatic solutions for acquiring data. You will be a key interface between our research roadmap and external data offerings. This role is based in our San Francisco HQ and will be part of a team of RPMs pushing the frontier of data acquisition. In this role, you will: Partner deeply with research: Work with researchers to scope data needs, define success criteria, and translate priorities into clear execution plans. Shape the data acquisition pipeline: Identify, evaluate, and advance high impact data opportunities - balancing research value, feasibility, quality, and responsible execution. Unblock yourself: Move work forward even when the path is unclear — using technical judgement, creative problem solving, and scrappy execution to make progress while longer-term solutions are still forming. Build lightweight systems and visibility: Use SQL, Python, dashboards, and simple tooling to track performance, quality, and blockers. Drive technical roadmaps: Collaborate with engineers to enhance data platforms, resolve blockers, and ensure security best practices such as access management. Scale your impact: Equip vendors and internal teams with the context, standards, and operating rhythms needed to focus on the most important problems. You’ll thrive in this role if you: Are proficient in SQL and Python for analysing datasets, querying databases, building dashboards, and generating actionable insights. Are comfortable using APIs, automation, and AI tools such as Codex to accelerate workflows, remove manual overhead, and upskill quickly in unfamiliar technical areas.Experience sou

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 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,