Internal Audit And Sox Manager in United States

About the Team The Product Policy team is responsible for the development, implementation, enforcement, and communication of the policies that govern use of OpenAI’s services, including ChatGPT, GPTs, the GPT Store, Codex, and the OpenAI API. About the Role We are looking for a Research and Advisory Partnerships Lead to build and manage the relationships, partnerships, and advisory structures that bring independent external expertise into our product and policy decisions. 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 identify and engage researchers, civil society organizations, subject-matter experts, and other external stakeholders whose perspectives can strengthen how we develop and deploy AI. You will establish and manage advisory councils, develop research partnerships with the academic community, and work closely with internal teams to translate external insights into actionable guidance. This role sits at the intersection of product, policy, research, and governance. It is well suited to someone who is comfortable building relationships across disciplines and designing processes that ensure outside expertise meaningfully informs internal decision-making. This role can be 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. In this role, you will: Develop, launch, and manage external advisory councils and other governance mechanisms that provide structured input on product and product policy. Build and maintain relationships with external experts, researchers, civil society organizations, and other stakeholders who can inform high-priority product and product policy decisions. Identify when external consultation can improve internal decision-making, and develop engagement strategies tailored to specific products, policy questions, and emer

About the Team OpenAI’s mission is to ensure that general-purpose artificial intelligence benefits all of humanity. The Engineering Acceleration team builds products that multiply the effectiveness of OpenAI’s technical teams, helping engineers, researchers, and product teams understand complex systems, learn from what they ship, and operate reliably at scale. As AI changes how software is built, we have an opportunity to rethink engineering workflows from first principles. We’re creating tools and shared systems that turn complex data, experimentation, and technical workflows into clear decisions and useful action. About the Role In this role, you’ll lead design across two connected product areas: a real-time data exploration and observability experience for investigating large-scale system and product behavior, and an experimentation platform for safely launching changes, measuring their impact, and deciding whether to ramp, iterate, or roll back. This is more than a dashboard-design role. You’ll define the interaction models that take someone from a vague question or unexpected signal to a trustworthy answer and clear next step. You’ll work closely with engineers, researchers, data scientists, and product teams to understand the mechanics of their work and make dense technical systems coherent without flattening the details that matter. You’ll also help establish greater consistency across OpenAI’s enterprise and internal tools, developing durable patterns that support AI-native workflows and enable other designers to build more effectively. This role is based in our Seattle, WA or San Francisco, CA offices. We offer relocation assistance to new employees. In this role, you will: Lead end-to-end design for data-intensive products used by engineers, researchers, and product teams. Shape the complete learning loop: instrument, launch, observe, investigate, evaluate, decide, and iterate. Create clear, high-craft workflows for querying, filtering, comparison, drill-d

About the team OpenAI’s Forward Deployed Engineering team partners with healthcare organizations to deploy production AI systems across clinical, operational, and member-facing workflows. We work at the boundary of customer deployment and core platform development, using customer engagements to define repeatable architectures, evaluations, integrations, and operating standards for complex, regulated healthcare environments. About the role We are hiring a Forward Deployed Engineer (FDE) to own end-to-end deployments of our models within healthcare organizations, including payers, providers, health systems, and healthcare technology companies. You will lead technical discovery, architecture, implementation, evaluation, productionization, and handoff, translating complex customer workflows, data, infrastructure, and regulatory constraints into production AI systems. You will measure success through production adoption, measurable workflow impact, and evaluation loops that establish customer-specific benchmarks, acceptance criteria, and launch readiness. You’ll collaborate directly with customer technical and operational teams, alongside internal Business, Research, Product, Engineering, and Security partners, to deliver solutions and translate deployment learnings into product improvements. This role owns the technical solution; ownership of the commercial or executive relationship is not required. This role is based New York City. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own the technical solution end to end, from customer discovery and workflow scoping through architecture, hands-on implementation, evaluation, production deployment, adoption, and handoff. Partner credibly with customer engineers, operators, and domain experts to frame ambiguous problems, define scope, and translate payer, provider, or health-system workflows into technical requirements and measurab

About the Team OpenAI’s Forward Deployed Engineering team partners with healthcare organizations to deploy production AI systems across clinical, operational, and member-facing workflows. We work at the boundary of customer deployment and core platform development, using customer engagements to define repeatable architectures, evaluations, integrations, and operating standards for complex, regulated healthcare environments. About the Role We are hiring a Forward Deployed Engineer (FDE) to own end-to-end deployments of our models within healthcare organizations, including payers, providers, health systems, and healthcare technology companies. You will lead technical discovery, architecture, implementation, evaluation, productionization, and handoff, translating complex customer workflows, data, infrastructure, and regulatory constraints into production AI systems. You will measure success through production adoption, measurable workflow impact, and evaluation loops that establish customer-specific benchmarks, acceptance criteria, and launch readiness. You’ll collaborate directly with customer technical and operational teams, alongside internal Business, Research, Product, Engineering, and Security partners, to deliver solutions and translate deployment learnings into product improvements. This role owns the technical solution; ownership of the commercial or executive relationship is not required. This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role, you will: Own the technical solution end to end, from customer discovery and workflow scoping through architecture, hands-on implementation, evaluation, production deployment, adoption, and handoff. Partner credibly with customer engineers, operators, and domain experts to frame ambiguous problems, define scope, and translate payer, provider, or health-system workflows into technical requirements and mea

About the team The Capital Markets team develops the financing strategy, solutions, and partnerships needed to support our expanding global AI infrastructure platform and long-term investment plans. About the role We’re looking for a structured finance professional to serve as a technical execution engine for a lean, high-impact capital markets team. In this role, you’ll own the models, analysis, diligence, process management, and key execution workstreams behind standardized or more “vanilla” financings, while partnering with senior transactors on more complex transactions. This is not a junior analyst role. You’ll need the experience and maturity to work directly with senior leaders, banks, investors, counsel, and advisors without multiple layers of review. You should be highly capable in the details, strong under transaction intensity, and ready to help build financing processes for a rapidly scaling AI infrastructure platform. What you’ll do Translate financing objectives into clear analyses, recommendations, timelines, and deliverables. Support senior transactors on complex financings, including structuring, documentation, diligence, negotiation, and closing. Lead analysis, diligence, process tracking, and execution workstreams for financing transactions. Own transaction models, including debt sizing, cash-flow waterfalls, sensitivities, covenant analysis, and scenario evaluation. Work directly with internal stakeholders, banks, investors, counsel, advisors, and other counterparties. Review transaction documentation and help ensure commercial, financial, and diligence details are reflected accurately. Manage high-volume, detail-intensive workstreams in a lean team environment. Help develop repeatable tools, processes, and analytical infrastructure as the capital markets function scales. You might thrive in this role if you have At least 4-6 years of directly relevant experience in project finance, structured finance, infrastructure finance, private equity, or a

About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Security team protects OpenAI’s technology, people, and products. We are technical in what we build but are operational in how we do our work, and are committed to supporting all products and research at OpenAI. Our Security team tenets include: prioritizing for impact, enabling researchers, preparing for future transformative technologies, and engaging a robust security culture. About the Role Trusted Computing and Cryptography is a core security team at OpenAI focused on deploying high-performance cryptography at scale, secure key management, and trusted hardware enclaves—from boot measurements to GPU confidential computation. As a Hardware Platform Security Architect, you’ll own hardware platform security at OpenAI. In this role, you will: Co-Architect Secure Silicon: Collaborate with cross-functional silicon teams (Silicon Design, DV, FW) and silicon partners (silicon test facilities, foundries) to develop secure silicon that meets the end-to-end system requirements. Co-Architect Secure Hardware: Collaborate with hardware vendors and cross-functional teams (kernel, compiler, infra) to design secure hardware that meets performance and security needs. Co-Architect Secure Systems: Architect and deploy systems using TPM2, Secure Boot, Nitro Enclaves, Intel SGX, AMD-SEV, and other secure hardware technologies. Drive Innovation: Engage with internal and external partners to align hardware innovations with OpenAI’s trusted computing and cryptographic requirements. You might thrive in this role if you have: 10+ years of industry experience in hardware security or hardware–software co-design. Proven expertise in deploying secure hardware systems at scale and integrating secure hardware primitives. Strong coding skills in Rust and/or C/C++, with proficiency in Python. Proven ability to collaborate across teams, architect solutions,

About the Team The Capital Markets team develops the financing strategy, solutions, and partnerships needed to support our expanding global AI infrastructure platform and long-term investment plans. About the Role We’re looking for a senior structured finance leader to create immediate execution leverage for a growing capital markets function. In this role, you’ll take broad financing objectives, such as raising a large pool of capital from a defined set of counterparties, and independently turn them into well-run transaction processes. You’ll lead complex financings from strategy through close, manage counterparties and advisors, and bring sound judgment to capital structure, risk allocation, process design, and execution. This is a hands-on role for someone who is still close to the details, not a purely senior relationship manager. Your work will allow the team lead to spend less time in day-to-day execution and more time building the broader capital markets organization. In this role, you will: Lead large, complex financing processes from initial structuring through diligence, negotiation, documentation, and closing. Translate broad capital-raising objectives into executable financing plans, timelines, work streams, and counterparty strategies. Manage lenders, investors, advisors, counsel, and internal stakeholders across high-stakes transactions. Provide oversight on financial structuring, modeling, diligence, risk allocation, and transaction documentation. Make clear recommendations on financing strategy, counterparty selection, process design, and tradeoffs. Operate effectively in a small, high-impact team without relying on a large analyst or associate bench. Help build repeatable internal processes for a financing function that is still scaling. Coach and develop more junior transaction professionals. You might thrive in this role if you have: 8-15 years of experience executing structured finance, project finance, infrastructure finance, digital infrastruct

About the Team OpenAI’s GTM Partnerships team builds a strategic, global partner ecosystem that accelerates customer success, enables enterprise AI adoption, and drives durable growth in support of OpenAI’s mission. Cloud partners are central to how customers discover, purchase, deploy, and scale OpenAI solutions. We work across cloud providers and their field, product, marketplace, technical, and partner organizations to reduce friction for customers and create repeatable paths from initial interest to production impact. The team collaborates closely with Sales, Technical Success, Product, Engineering, Finance, Legal, Security, Marketing, Operations, and Customer Success to turn strategic cloud relationships into measurable customer and commercial outcomes. About the Role We are hiring a Partner Director, GTM Cloud Partnerships to shape and execute OpenAI’s go-to-market strategy with strategic cloud partners. You will own senior relationships across a portfolio of cloud providers and develop joint business plans that expand customer access to OpenAI’s products, generate partner-sourced opportunities, and accelerate enterprise adoption. You will translate company-level partnerships into practical field motions spanning account planning, co-selling, cloud marketplaces, customer procurement, technical enablement, solution development, and executive engagement. This is a highly strategic and hands-on role. Success requires executive presence, strong commercial judgment, cloud ecosystem expertise, and the operating discipline to coordinate complex initiatives across multiple partners, regions, and internal teams. The ideal candidate can move fluidly between long-term strategy and the detailed execution required to deliver measurable results. This role is based in San Francisco. We use a hybrid work model of three days in the office per week. In this role, you will: Own the strategic and commercial relationships with a top global cloud partner, establishing strong alignm

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 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 Codex is OpenAI's software engineering agent. Codex Security extends that work into one of the most important product areas in AI: helping organizations find, validate, prioritize, and fix real vulnerabilities in the software they build and depend on. The Codex Cyber team is building the product and platform foundations for AI-native application security. This includes Codex Security product experiences, cloud-based security analysis, platform controls across Codex, customer deployment and support tooling, and infrastructure that helps security researchers and cyber models improve over time. The team is early, small, and growing quickly, with a mandate to move fast and hire exceptional builders. About the Role We are looking for software engineers first: strong full-stack or product-minded generalists who can own ambiguous product and platform problems end to end. Security experience is helpful, and security curiosity is important, but this is not a role for security specialists who only occasionally write code. The right person is an excellent builder who is excited to work in security and can turn complex research, product, and customer needs into reliable systems. You will work across user-facing product surfaces, developer workflows, backend services, security analysis pipelines, cloud infrastructure, and internal tooling. You may build features that make Codex Security more useful for application security teams, systems that scale cloud-based security analysis, platform controls that make agentic coding safer, or infrastructure that helps security researchers and models become more effective. You will collaborate closely with engineering, product, security research, infrastructure, and customer-facing partners as Codex Cyber becomes a major product and platform investment for OpenAI. In this role, you will: Build end-to-end product features for Codex Security, from developer-facing interfaces to APIs, backend services, and workflow tooling. Own a

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 OpenAI's Marketing team helps customers understand, adopt, and get value from OpenAI's products and platform. The SMB Ads Marketing team is building the growth engine for small and medium-sized business advertisers: helping them discover the platform, sign up, launch campaigns, understand performance, and grow spend over time. We take a data-driven approach to understanding customer needs, market dynamics, and funnel behavior. We partner closely with Product, Engineering, Data Science, Sales, Partnerships, Marketing Operations, Design, and Communications to create a cohesive end-to-end advertiser experience and help businesses unlock value from OpenAI's advertising platform. About the Role We are hiring a Growth Marketing Manager, SMB Ads to help build and execute high-velocity growth programs for small business advertisers. This person will work across acquisition, activation, lifecycle, and conversion, with an initial focus on helping advertisers move from interest and sign-up to first meaningful spend & retention over time This is a hands-on growth role for someone who loves turning ideas into shipped experiments. You will build campaigns, lifecycle journeys, landing page tests, messaging tests, audience experiments, AI-assisted workflows, reporting improvements, and practical conversion programs. As the SMB Ads business grows, this role may continue to support acquisition and activation and expand deeper into same-store growth, lifecycle, retention, and repeat spend. In This Role, You Will: Execute growth experiments across acquisition, activation, lifecycle, and early retention. Build email, in-product, landing page, audience, messaging, and offer tests that help SMB advertisers reach first spend and repeat value. Use AI tools to prototype marketing assets, automate workflows, analyze funnel data, generate creative variations, and build internal growth systems. Partner with Growth, Product, Engineering, Data Science, and Marketing Operations

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

About the Team The Post-Training Frontiers team is responsible for training the frontier agents OpenAI ships to the world (GPT-Next). We train the flagship agentic models behind Codex, ChatGPT, and the API through large-scale reinforcement learning. The team’s work spans four areas. First, execution and science: working with teams across OpenAI to decide what can go into the final model and how, using scientific experiments and evals that are representative of the final pipeline so issues can be recognized early. Second, RL scaling: executing the final large-scale reinforcement learning run, making sure GPUs are used efficiently and training stays healthy. Third, research: improving horizontal capabilities like instruction following, factuality, memory, and multi-agent behavior, where the team’s broad visibility helps identify cross-cutting improvements across teams and domains. Fourth, engineering: maintaining the infrastructure stack and internal tools to ensure that both the final run and all integrations go as smoothly as possible and that the systems are easy to work with. About the Role This role focuses on keeping our frontier RL training runs fast, reliable, and unblocked. You will work across engineering and infrastructure problems as they emerge, from scaling and orchestration issues to inference bottlenecks, numerical problems, and hardware failures, as well as supporting large horizontal integrations in the big run, like multi-agent capabilities or memory. This is a role for a strong generalist who quickly learns anything needed for the task, has high attention to detail, debugs deeply, and is motivated by fixing the highest-impact problem in front of the team. In this role, you will: Keep large-scale async RL training runs moving by jumping into the most urgent engineering and infrastructure problems. Debug issues across training systems, inference, orchestration, scaling, and distributed infrastructure. Improve the reliability and efficiency of RL trai