Engineering Access Requests Team Manager in United States

About the Team OpenAI Finance ensures the organization is positioned for long-term success as we pursue our mission. The Order to Cash (OTC) team oversees the complete flow of commercial transactions from order intake and provisioning through billing, collections, and cash application — ensuring accuracy, compliance, and operational excellence in support of OpenAI’s mission to ensure artificial general intelligence benefits all of humanity. About the Role We are looking for a senior, hands-on operator to own Order Management and Billing execution across OpenAI’s cloud marketplace and partner ecosystem, including platforms such as AWS, GCP, Oracle Cloud, GovCloud, and future channels. This senior individual contributor role will translate partner requirements into scalable workflows and ensure launch readiness, accurate billing, and reliable daily execution. As a senior individual contributor within the Cloud Marketplaces team, you will own the end-to-end order-to-invoice lifecycle for your assigned portfolio. You will ensure that private offers, commercial terms, provisioning, pricing, usage, billing data, credits, settlements, and partner-specific reporting flow through our systems accurately, on time, and with audit-ready controls. You will implement and continuously improve the common cloud marketplace operating model, lead cross-functional execution for your assigned portfolio, and surface risks, requirements, and improvement opportunities. You will partner across Revenue Systems, Product, Engineering, GTM, Finance, Partner Operations, and external marketplace stakeholders. This role is critical to building the operational backbone for OpenAI’s expansion across cloud marketplaces and government-cloud channels. You will combine deep operational judgment with process and control execution, automation, clear communication, and hands-on problem solving to improve billing reliability, partner experience, customer outcomes, and financial integrity at scale. This role

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 We’re looking for a software engineer to help build the design methodology, software abstractions, and infrastructure that enable a small silicon team to develop complex chips rapidly and with high confidence. You will turn evolving architecture and design needs into reusable tools and workflows that improve iteration speed, quality, and then apply those tools to help construct world-class silicon. You’ll work closely across architecture, design, verification, performance modeling, and systems software. This role is well suited for an engineer who enjoys building high quality software and is motivated by the challenge of improving velocity and quality of the silicon development process. In this role, you will: Develop and scale design methodologies for rapid first-party chip development and apply them to construct complex custom chips Create abstractions that allow hardware structures, configurations, experiments, and results to be represented consistently across tools. Automate high-value engineering workflows and improve their reproducibility, observability, testability, and ease of use. Partner with architects, RTL designers, verification engineers, compiler engineers, and systems software engineers to gather requirements and then implement solutions. Use methodology and tooling to identify design risks early, accelerate iteration, and improve confidence in performance and implementation tradeoffs. Contribute across multiple aspects of software and hardware

About the Team OpenAI Finance ensures the organization is positioned for long-term success as we pursue our mission. The Order to Cash (OTC) team oversees the complete flow of commercial transactions from order intake and provisioning through billing, collections, and cash application — ensuring accuracy, compliance, and operational excellence in support of OpenAI’s mission to ensure artificial general intelligence benefits all of humanity. About the Role We are seeking a Senior Manager to build and scale Order to Cash across OpenAI’s API and ChatGPT businesses, cloud marketplaces, and strategic partnership channels. This role will own end-to-end Order Management and Billing operations across API and ChatGPT while leading OTC readiness and execution for AWS Marketplace, Google Cloud Marketplace, Oracle Cloud Marketplace, GovCloud, and future partner channels. The role will also own the end-to-end Order Management and Billing close, setting the close calendar, readiness standards, review and sign-off expectations, while leading the team responsible for execution. You will oversee the Order Management and Billing lifecycle across API, ChatGPT, marketplace, and partner transactions, spanning commercial readiness, order intake, provisioning, usage and transaction data, pricing validation, invoicing, credits, settlements, and product and partner reporting. Your work will ensure transactions are accurate, timely, complete, and supported by audit-ready controls. This is a leadership role that combines strategic ownership, cross-functional leadership, and hands-on operational execution. You will define the target operating model, lead first-of-kind launches, shape product and systems roadmaps, and oversee the resolution of complex contract modifications, non-standard pricing, usage disputes, reconciliation breaks, settlement variances, and customer- or partner-impacting escalations. You will collaborate with teams across Finance, GTM, Product, Engineering, Legal, Tax, Reven

About the Team The GTM Intelligence Solutions team builds the data and decision systems that help customer-facing teams take the right action at the right time. We combine product telemetry, commercial data, customer context, and field activity to identify account health and opportunity, recommend actions and use cases, deliver intelligence through field-facing products and agent workflows, and measure what happens next. We’re looking for a Data Scientist to help build the next generation of GTM intelligence at OpenAI. You will own a flexible portfolio of high-impact decision data products and work closely with Technical Success and other GTM teams to ensure the work drives better decisions. About the Role As a Data Scientist on GTM Intelligence Solutions, you will define and build the intelligence systems that help customer-facing teams prioritize accounts, identify risks and opportunities, choose interventions, and understand what worked. You will set the roadmap and methodology, build canonical features, ship reliable production workflows, monitor quality and adoption, and improve the systems using field feedback and business outcomes. This role combines hands-on technical depth with strong product and business judgment. You should be as comfortable writing production Python and advanced SQL, defining durable data contracts, and operating decision products as you are evaluating a ranking approach or designing an experiment. You will personally ship reliable first versions and partner with Analytics Engineering and Data Engineering when work requires shared infrastructure or additional scale. In This Role, You Will Set the roadmap and methodology for GTM intelligence and decision products, using deep stakeholder discovery to probe beyond stated requests, uncover the underlying decisions, workflows, constraints, and measures of success, and translate them into measurable systems. Own the full lifecycle of intelligence products, including feature definition, methodo

About the Team API Multimodal builds the developer-facing products and infrastructure that bring OpenAI’s image, audio, and real-time model capabilities into the world. We are responsible for high-scale APIs for image generation, speech transcription, speech generation, and low-latency voice interactions. We partner closely with Research and Inference to bring frontier model capabilities to developers and use customer feedback to improve our models. About the Role As a software engineer on API Multimodal, you will build and operate the products and distributed systems behind OpenAI’s image, audio, and real-time APIs. You will work across model integration, API design, and production infrastructure to turn new research capabilities into reliable developer experiences. This hands-on role combines backend and systems depth with product judgment: you will own projects end to end, partner with Research, Inference, and Safety, and help make multimodal AI useful at scale. Model training experience is not required. In this role, you will: Design, build, and ship developer-facing APIs and backend services that serve frontier models. Architect low-latency streaming, request, session, and model integration systems that make complex multimodal interactions reliable and intuitive at scale. Work directly with Research to bring new model capabilities into production, shape the systems around them, and incorporate feedback from real-world developers and customers. Own the availability, latency, scalability, and cost efficiency of the services you build. Own projects from technical design and implementation through launch and ongoing iteration, while raising the team’s engineering standards. Your background might look something like: 7+ years of professional experience, excluding internships, in backend, infrastructure, platform, or product engineering roles. A track record of designing, building, and operating production backend services, developer-facing APIs, or distributed syste

About the Team OpenAI is a frontier AI research and deployment company. Frontier research is at the center of how we advance our mission, with researchers, engineers, product leaders, operators, and many other teams working together to turn new capabilities into systems that benefit humanity. The People team helps OpenAI attract, engage, and support the exceptional talent this work requires. Employer Brand sits at the intersection of Research, Recruiting, Communications, Marketing, and Brand. Its mandate is to continue to establish OpenAI in the talent market as the unique and leading frontier research lab—not simply another technology company—and make our distinctive research environment, mission, culture, and opportunity for impact relevant and tangible to every priority talent audience. About the Role We’re hiring an Employer Brand Manager to build and scale the strategy, narrative, and operating system that shape how priority talent understands OpenAI. This senior individual contributor will anchor our employer brand in OpenAI’s identity as a frontier research lab and translate an evidence-backed “why OpenAI / why now” narrative into campaigns, researcher and employee stories, recruiter and hiring manager enablement, and candidate experiences. This role is especially important as OpenAI competes for exceptional talent across research, engineering, product, and other mission-critical functions in a fast-moving field where external perceptions can be incomplete or change quickly. You will develop a clear, credible talent narrative for priority audiences—anchored in frontier research and substantiated by individual agency, world-class infrastructure, research-to-product translation, deployment scale, and a willingness to answer hard questions candidly. This role is responsible for ensuring the external brand resembles our culture and ethos internally, therefore must remain immersed in various OpenAI research and applied branches. This role is based in San Francisco

About the Team OpenAI’s Business organization works with customers and partners on some of our most complex and consequential opportunities. These efforts require rigorous strategy, strong operating leadership, and coordinated execution across commercial, product, technical, deployment, and go-to-market teams. About the Role We are hiring a Business Lead to serve as the operating leader for a strategically important initiative anchored in a major partnership. This person will turn an ambitious, cross-functional mandate into a clear strategy, operating plan, decision structure, and set of measurable outcomes. This role combines strategy and operations, product judgment, commercial skills, and the ability to get things done. You will identify the most promising product and customer opportunities, develop a point of view on how our products should work together, shape the commercial approach, and personally drive execution across both organizations. This is a hands-on role for someone who wants to own outcomes, not just coordinate work. You will structure ambiguous problems, establish priorities, build trusted relationships with internal and external stakeholders, and work across product, engineering, deployment, and go-to-market teams to remove blockers and deliver results. Success means establishing a durable operating model for the initiative, improving decision velocity, translating strategy into coordinated execution, launching a joint go-to-market motion, landing an initial cohort of customers, and delivering a high-quality enterprise deployment. In this role, you will: Own the initiative’s integrated strategy and operating plan, including priorities, desired outcomes, metrics, owners, dependencies, and decision points Structure complex and ambiguous business problems, develop fact-based recommendations, and translate them into clear choices and executable plans Define success measures and build operating reviews that surface progress, risks, tradeoffs, and requi

About the Team OpenAI's mission is to ensure that AGI benefits all of humanity. The Business Systems team helps make that mission possible by building the internal products and platforms that allow OpenAI to operate with speed, reliability, and care. We build internal applications and workflows for Finance and Supply Chain. Our work spans product discovery, React and TypeScript interfaces, Python services and APIs, data models, workflow orchestration, enterprise integrations, and the systems that connect people to systems of record. We work directly with the people who use these products and care about correctness, permissions, auditability, and production reliability. Examples of our work include building an integration platform for supply chain integrations, integrations with Oracle Fusion and Zip, contract intelligence applied to B2B revenue recognition, and Temporal-based agentic workflows for credit checks, duplicate bank detection, and invoice triaging. We turn these efforts into reusable patterns that can support many workflows, rather than one-off automations. About the Role We are looking for Product Engineers to build internal applications end to end. This role spans product discovery, user experience, frontend, backend services, data models, workflow orchestration, and integrations with order management, fulfillment, and supply chain systems. You will take a problem from a first conversation with a Finance or Supply Chain partner through design, implementation, rollout, and production support. Strong candidates combine product judgment with engineering depth. You should be comfortable moving between a React interface, a Python API, a durable workflow, and an integration with an enterprise system. You should be able to ship a useful first version quickly while building the foundations for reuse, security, and long-term maintainability. Direct AI experience is helpful, but the core requirement is strong product engineering judgment and reliable execution. I

About the Team OpenAI’s GTM Data Science team helps shape how our products are adopted, monetized, and scaled across organizations. We work at the intersection of Product, Go-to-Market, Finance, Research, and Data, turning product usage, customer evidence, and market signals into decisions that grow durable enterprise value. We’re looking for a senior Data Scientist to own the analytical strategy for enterprise knowledge-worker adoption. As ChatGPT Work and Codex become capable of research, analysis, document creation, spreadsheets, presentations, internal knowledge synthesis, and other agentic workflows, you will help determine how these products become embedded in everyday work—not merely tried once. About the Role You will define how we measure activation, retained usage, workflow depth, and value across ChatGPT Work, Codex, and connected enterprise systems. You will explain why adoption succeeds or stalls and identify the product, enablement, and commercial interventions most likely to create durable usage. This is a hands-on, zero-to-one role. You will work through imperfect telemetry, overlapping product surfaces, evolving definitions, and ambiguous business questions. You will partner closely with GTM, Product, Finance, Research, Customer Deployment, Analytics Engineering, and Data Science. Your work is successful when it changes a product, GTM, or investment decision. In This Role, You Will Define a trusted measurement framework for knowledge-worker adoption, including identity, eligible populations, activation, retained usage, penetration, workflow depth, feature adoption, and monetization. Map the knowledge-worker journey from initial exposure through first successful task, repeated workflows, multi-surface usage, and durable adoption. Identify which personas, functions, use cases, product capabilities, and account conditions are associated with deep and retained usage. Design and evaluate experiments and quasi-experiments across onboarding, enablement, wo

About the Team The Personal AGI team is responsible for training and improving pre-trained models to be deployed into ChatGPT, the API, and potential future products. In the Model Experience team, we shape the default character and behavior of ChatGPT: how the model communicates, responds to users, uses its capabilities, and behaves across different contexts and languages. Our goal is to make every interaction with ChatGPT thoughtful, helpful, and trustworthy. We take an opinionated view of what good human–AI interaction should look like, then turn that vision into real model behavior through human data, evaluations, reward models, and post-training. Our work sits at the intersection of research, product, and model design. We partner closely with teams across OpenAI to conduct research and ensure our models are thoughtful, safe, reliable to serve millions of users. About the Role As a Research Engineer / Scientist, you will research and develop improvements to our models. Our team works in research areas combining reinforcement learning and products. We're looking for individuals with strong ML engineering skills and research experience, especially with novel and highly capable models. An ideal candidate is passionate about product-driven research and the quality of human-AI interaction. 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: Own and pursue a research agenda to improve model capability and performance. Collaborate closely with the other research and product teams, allowing customers to optimize their own models. Build robust evaluations for tracking modeling improvements. Design, implement, test, and debug code across our research stack. You might thrive in this role if you: Have a deep understanding of machine learning and machine learning applications. Have good judgment about model behavior and can communicate this judgment effec

About the Team OpenAI’s Education team is building products that advance how people learn with AI. The team works across higher education institutions, K-12 districts, and country-level partnerships, including applied research on how AI affects learning and cognitive outcomes. The team owns owns ChatGPT Edu, ChatGPT for Teachers, and related product/research work. The team partners closely with go-to-market, research, Consumer Learning, and model teams to turn education-specific insights into product experiences that can improve ChatGPT more broadly. Some of our recent work: New Education Plugins for ChatGPT Work and Codex New tools for understanding AI and learning outcomes Education for countries Advancements in higher education Early product work - Introducing Study Mode About the Role We’re looking for a hands-on Tech Lead Manager to lead and manage a team of senior full-stack engineers building AI-native learning experiences in ChatGPT. This person will combine technical execution, product judgment, and people leadership: they will write and ship code, manage engineers, and help shape the product direction for how students and Educators use AI. In This Role, You Will Lead and manage a team of three senior full-stack engineers. Build product experiences for ChatGPT Education, ChatGPT for Teachers, and AI-native learning workflows. Partner with research teams on field studies, randomized control trials, classifiers, data pipelines, and cognitive-outcome measurement. Collaborate with Consumer Learning and model teams to translate education insights into broader ChatGPT behavior and product improvements. Drive execution across product, engineering, research, go-to-market, and partner teams. Help define product strategy, priorities, and delivery plans for a new product pod. You Might Thrive In This Role If You Have several years of direct people-management experience with engineers. Are still highly technical and comfortable doing IC engineering work. Have strong pr

About the Team Our Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve people's lives. About the Role We are seeking a lead thermal simulation engineer to help accelerate the design and development of next-generation robotic systems through modeling, simulation, and analysis. You will work closely with mechanical, electrical, controls, and robotics engineers to evaluate designs before hardware is built, identify risks early, and guide critical architecture decisions. This role spans structural and thermal analysis and design across robotic subsystems including actuators, mechanisms, structures, electronics, and integrated systems. You will develop simulation workflows that improve engineering velocity, increase confidence in design decisions, and help us build more capable, reliable, and manufacturable robotic platforms. 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: Perform thermal simulations to assess heat generation, cooling strategies, thermal interfaces, and system-level thermal performance Partner with mechanical, electrical, and controls engineers to influence design decisions early in development Build simulation models to evaluate robotic actuators, transmissions, mechanisms, structures, soft goods, and integrated assemblies Correlate simulation results with physical testing and develop methodologies to improve model accuracy Support architecture trade studies by evaluating design concepts before hardware is built Develop simulation workflows, standards, and best practices that scale across the robotics o

About the Team OpenAI, in close collaboration with our capital partners, is embarking on a journey to build the world’s most advanced AI infrastructure ecosystem. The Stargate team is central to this mission, setting the core infra strategy and implementing this vision. From site selection to the buildout process, this team sits at the intersection of commercial, technical, strategy, and operations, interacting with teams and executives inside and outside of OpenAI. About the Role The New Geography and International Growth Lead will own the strategy for infrastructure expansion into new geographies, including market assessment, stakeholder engagement, and coordination across energy, policy, commercial, and other infrastructure workstreams. This role identifies and enables priority international growth opportunities while ensuring alignment with regional regulatory, operational, sustainability, and long-term infrastructure objectives. This is an individual contributor lead role and does not have direct reports initially. The role will translate ambiguous market-entry questions into clear recommendations, identify the conditions required for OpenAI to advance in new regions, and coordinate the cross-functional work needed to turn priority geographies into executable infrastructure options. Key Responsibilities Build market-entry frameworks for international infrastructure geographies, including power availability, land readiness, regulatory posture, commercial fit, and execution risk. Assess priority regions and countries against OpenAI’s long-term compute, energy, sustainability, policy, and operational objectives. Coordinate cross-functional geographic diligence with energy, policy, commercial, legal, finance, procurement, engineering, and site-readiness stakeholders. Lead early stakeholder mapping and engagement strategy with utilities, regulators, government entities, developers, capital partners, and other market participants. Translate regional findings into exe

About the Team OpenAI’s Cyber team works to make frontier AI a decisive advantage for defenders. The Cyber Blue Team is an operator-led group focused on turning real defensive problems into better models, useful products, safe Codex workflows, and integrations with the security tools defenders already use. Our ambition is simple: Raise attacker cost. Lower defender toil. Prove it by defending OpenAI; scale it through the ecosystem. We are not setting out to build another SIEM or autonomous SOC. We want to build the AI reasoning and workflow layer that helps security teams investigate threats, create and validate detections, improve their controls, and respond with greater speed and confidence. About the Role We are looking for a Product Manager to help build a new generation of AI-powered cyber defense products. You will work closely with security practitioners, researchers, engineers, designers, internal security teams, customers, and technology partners to turn emerging model capabilities into products that solve meaningful defensive problems. This is an early-stage product role. The work will span product discovery, prototyping, evaluation, development, launch, and iteration. You will help the team identify where AI can create the most value for defenders and translate those opportunities into clear, usable, and trustworthy product experiences. Initial areas of focus may include: Detection engineering and detection-content development Threat hunting and investigation Security validation and control testing AI-agent and MCP runtime defense Integrations with security platforms and enterprise workflows Safe, governed assistance for incident response The specific roadmap will continue to evolve based on model progress, practitioner needs, internal learnings, and customer feedback. In This Role, You Will Work with security practitioners to understand high-value defensive workflows, recurring pain points, and opportunities for AI to materially improve outcomes. Help sh

About the Team Training Runtime designs the core distributed machine-learning training runtime that powers everything from early research experiments to frontier-scale model runs. With a dual mandate to accelerate researchers and enable frontier scale, we’re building a unified, modular runtime that meets researchers where they are and moves with them up the scaling curve. Our work focuses on three pillars: high-performance, asynchronous, zero-copy tensor and optimizer-state-aware data movement; performant, high-uptime, fault-tolerant training frameworks (training loop, state management, resilient checkpointing, deterministic orchestration, and observability); and distributed process management for long-lived, job-specific and user-provided processes. We integrate proven large-scale capabilities into a composable, developer-facing runtime so teams can iterate quickly and run reliably at any scale, partnering closely with model-stack, research, and platform teams. Success for us is measured by raising both training throughput (how fast models train) and researcher throughput (how fast ideas become experiments and products). About the Role As a Training: ML Framework Engineer, you will work on improving the training throughput for our internal training framework, while enabling researchers to experiment with new ideas. This requires good engineering (for example designing, implementing, and optimizing state-of-the-art AI models), writing bug-free machine learning code (surprisingly difficult!), and acquiring deep knowledge of the performance of supercomputers. In all the projects this role pursues, the ultimate goal is to push the field forward. We’re looking for people who love optimizing performance, understanding distributed systems, and who cannot stand having bugs in their code. Since our training framework is used for large runs with massive numbers of GPUs, performance improvements here will have a large impact. This role is based in San Francisco, CA. We use a