Executive Team Leader Specialty Sales in San Francisco

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 Strategic Initiatives & Operations team is in need of a Technical Program Manager (TPM) to streamline our processes, including full safety governance and integration of various safety research and mitigations into our ChatGPT, API, and any frontier models. This role is critical for driving safe deployment of our new models, synthesizing inputs from multiple stakeholders, ranging across research, product, engineering, legal and policy, and ensuring all the risks are effectively and properly monitored, mitigated or resolved. About the Role As a TPM, you will be responsible for critical tasks ranging from tracking safety research progress and risk tables to overseeing the quality of human data campaigns – acting as the connective tissue to enhance the deployment of OpenAI’s safety system. Additionally, you will create and execute a compute roadmap for your team to ensure that our top priorities are resourced while taking advantage of new opportunities to make key safety research discoveries. Your primary focus will be to ensure our models are qualified for safe deployment. 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: Manage key risk areas and corresponding stakeholders. Keep track of a stack of existing and future mitigations for every major product and model deployment. Standardize the lifecycle of risk assessment, setting safety bars, consolidating inputs from multiple stakeholders across research, product, engineering, legal and policy, pre-launch safety reviews and post-launch followup. Manage pre-launch safety reviews. Share launch calendars and key safety practices and evaluations with our key parter (i.e. Microsoft). Develop comprehensive documentation for all the safety work, including metrics, evaluations, and progress tracking across multiple teams within OpenAI. Help with publishing and open sourcing safety

About the Team API Agents builds the shared agent harness, tools, and infrastructure that turn OpenAI’s frontier models into systems that can reliably complete real work. We carry the capabilities behind Codex into a much broader set of products and workflows across software engineering, research, finance, healthcare, enterprise operations, and more. Our work spans search and connected context, computer use, memory, delegation and multi-agent coordination, and safe execution. Sitting at the intersection of Research, Codex, infrastructure, and applied product teams, we build reusable agent capabilities that compound across the ecosystem. About the Role We are looking for an experienced backend software engineer to build the core systems behind the next generation of agents. You will design reliable services and abstractions that help agents find the right context, use tools and computers, retain knowledge, coordinate over long-running workflows, and take action safely. The role combines deep backend and infrastructure work with strong product judgment, with opportunities to work across agent runtimes, orchestration, search, execution environments, identity and permissions, observability, and evaluations. This is software and systems engineering rather than model training: success comes from strong backend fundamentals, high agency, and the ability to turn fast-moving research capabilities into dependable production primitives. In this role, you will: Design, build, and operate the shared agent harness and backend infrastructure that power long-running, high-value workflows across OpenAI and third-party products. Build reusable capabilities across search and connected context, computer use, memory, tool execution, delegation, subagents, and multi-agent orchestration. Establish the foundations agents need to operate safely in production, including secure execution environments, identity and permissions, observability, evaluations, reliability, and cost and latency effi

About the Team Our economics team is continuously working to improve our understanding of an AI-driven economy. About the Role We are seeking a highly technical Economist to join the OpenAI Economic Research team studying the real-world economic impacts of AI. This role is designed for economists with up to 5 years of professional experience post-Ph.D. who are interested in using novel, large-scale datasets to study how AI is reshaping economic systems. We are looking for candidates with deep expertise in at least one core domain relevant to AI’s economic impact, and an interest in contributing to a broader research agenda spanning labor markets, firm behavior, market dynamics, and macroeconomic change. This is an individual contributor role where the candidate will organize and execute on their own data-oriented projects. You will work at the intersection of economic research, data science, and public policy to produce rigorous empirical work that informs decision-makers across the public, industry, and government. Research Areas of Interest We are particularly interested in candidates with demonstrated expertise in one or more of the following areas: Economic Measurement of AI Impact (e.g., adoption trajectories, labor market transitions, productivity growth, and forecasting/scenario modeling for AI-driven economic change) Macroeconomic Implications of AI (e.g., productivity, technology diffusion, economic growth) AI and the Labor Market (e.g., employment, wages, job search, task-level impacts, skill acquisition) Applicants are not expected to have experience across all domains. We aim to build a team with complementary strengths across these areas. In this role, you will: Design and execute empirical research using large-scale observational or experimental data. Apply causal inference and/or structural modeling techniques to study AI-driven economic change. Collaborate with cross-functional teams to translate research questions into testable frameworks and applic

About the Team OpenAI’s Industrial Compute organization is building the infrastructure required to support the next generation of frontier AI systems. Through a combination of strategic partnerships and self-built data center campuses, we are scaling the physical infrastructure needed to deliver compute at unprecedented scale. The Commissioning organization is responsible for ensuring this infrastructure is safely tested, validated, integrated, and transitioned into reliable operations. As the portfolio grows, the team is building common standards, processes, tools, and reporting systems that allow commissioning programs to operate consistently across projects while giving teams and leadership clear visibility into readiness, risk, and execution. About the Role We are seeking a Commissioning Program Manager to build and scale the operating systems behind OpenAI’s infrastructure commissioning programs. You will own the development and continuous improvement of commissioning standards, processes, tools, dashboards, and KPIs across the infrastructure portfolio. You will work closely with commissioning and construction teams to translate field execution needs into practical playbooks, workflows, templates, metrics, and reporting mechanisms that teams can use from construction readiness through testing and turnover. This role sits at the intersection of infrastructure delivery, program management, process design, and data. The ideal candidate understands how complex construction projects operate and can turn fragmented workflows and project data into repeatable systems that improve execution without creating unnecessary administrative burden. Key Responsibilities Develop and maintain commissioning program standards, playbooks, process maps, templates, checklists, stage gates, and acceptance criteria across infrastructure projects. Establish consistent workflows for commissioning planning, construction readiness, QA/QC, issue management, document control, testing evidence

About Team Our Robotics team is focused on unlocking general-purpose robotics and advancing toward AGI-level intelligence in dynamic, real-world environments. Working across the full model and systems 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 physical constraints of real-world systems to improve people’s lives. About Role We are building a supply-chain organization capable of supporting our transition from laboratory-scale development to factory-scale operations. We are looking for an Inventory Manager to build and operate our inventory function from the ground up. This is a highly hands-on role. In the near term, you may start with an empty room and be responsible for determining what racks, shelving, bins, labels, scanners, workflows, and systems are needed to turn it into a functional stockroom. You will receive material, organize inventory, perform counts, move parts between buildings, resolve discrepancies, and establish the processes others will eventually follow. As we grow, you will have the opportunity to develop this foundation into a full-scale, multi-site factory inventory operation. You may hire and manage contractors or onsite inventory administrators, but this role will initially have a significant individual-contributor component and will remain accountable for day-to-day execution. This role owns inventory and internal logistics. It does not own purchasing, production planning, or inbound and outbound supplier logistics. This role is based in San Francisco, CA and requires in-person presence 5 days a week. In this role you will: Build inventory operations from the ground up across various OpenAI facilities. Design and set up stockrooms, receiving areas, and material-storage locations, including selecting racks, shelving, bins, carts, labeling equipment, scanners, and other infrastructure. Personally execute core inventory

About the Team Critical Harm Operations sits within User Safety & Risk Operations and builds enforcement systems for Frontier Risk and Material Harm that are accurate, fast, defensible, and built to scale. We turn policy intent into operational readiness, review standards, quality systems, escalation paths, automation guardrails, and durable cross-functional operating models. About the Role We are looking for an exceptional Program Manager to help build durable operating systems and run some of OpenAI’s most complex safety operations. The core need is a high-agency operator who can take an ambiguous problem, create the right structure, align cross-functional partners, and drive the work through execution. This role will move across Critical Harm priorities as needs evolve. You may step into operationalizing national security or violent-activities workflows, support wellbeing and Frontier Risk initiatives, or help scale programs such as Trusted Access. Deep domain expertise is helpful but not required; the strongest candidates will learn quickly, exercise excellent judgment, and make complex programs move. In this role, you will: Lead strategic operational builds across priority workflows from problem statement to implemented operating model, including scope, owners, milestones, risks, success measures, and execution cadence. Translate policy, safety, technical, legal, and operational constraints into workflows, requirements, playbooks, escalation paths, and decision-making structures that teams can execute. Coordinate with User Ops leadership, Product Policy, Integrity, Safety Systems, i2, Legal, Product, Engineering, Support, vendors, and other partners to resolve dependencies and keep critical work moving. Move in and out of workflows as priorities shift—standing up new programs, stabilizing operations, improving handoffs, and transitioning durable ownership to the right team. Use operational data and frontline signals to identify bottlenecks, quality gaps, ca

About the Team OpenAI's Industrial Compute organization is building the world's most advanced AI infrastructure ecosystem. Through strategic partnerships and self-built campuses, we are scaling one of the world's fastest-growing AI infrastructure platforms. The Supply Chain organization ensures critical infrastructure components—from compute systems and networking equipment to integrated rack solutions—are sourced, manufactured, qualified, and delivered with the speed and reliability required to support frontier AI development. We partner closely with Hardware Engineering, Manufacturing Quality Engineering, Infrastructure Delivery, Hardware Operations, Finance, and suppliers worldwide to build a resilient, scalable supply chain capable of supporting rapid infrastructure expansion. As Industrial Compute continues to grow, Supply Chain serves as the operational bridge between engineering innovation and large-scale infrastructure deployment. About the Role We are seeking a Supply Chain Manager to lead strategic execution across sourcing, supplier operations, manufacturing quality, and infrastructure delivery for OpenAI's AI infrastructure portfolio. This role will oversee a multidisciplinary team responsible for strategic sourcing, manufacturing quality engineering, and technical program management while partnering closely with engineering, finance, hardware operations, and deployment teams. You will drive supplier strategy, manufacturing readiness, production planning, quality performance, and operational execution across the full hardware lifecycle. Success requires balancing long-term supplier strategy with day-to-day execution. You'll establish scalable operating mechanisms, strengthen supplier partnerships, manage complex cross-functional programs, and ensure OpenAI can rapidly deploy AI infrastructure without compromising quality, cost, or reliability. This is a people leadership role responsible for developing a high-performing organization while driving operati

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 The Treasury team is responsible for protecting liquidity, enabling scale, maintaining strong controls, and helping the company operate with clarity and resilience. We work across finance and operational partners to ensure funds move safely, visibility remains high, and Treasury infrastructure keeps pace with a fast-moving business. As hands-on operators and builders, we combine financial judgment with AI, automation, and data to solve problems faster, strengthen controls, and continuously improve how Treasury operates. About the Role We’re looking for a Treasury Manager to own and execute critical activities across OpenAI’s global treasury operations, including cash management, payments, bank account management, forecasting support, controls, and reporting. Beyond day-to-day operations, this person will support Treasury leadership on high-impact projects such as M&A integrations, new legal entity formation, and geographic and currency expansion. They’ll also help build scalable, AI-enabled systems, workflows, and controls for a rapidly growing global business. This is an individual contributor role with broad scope, spanning operational ownership and building an AI-native Treasury function. 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: Own core global treasury operations across cash positioning, payments, bank account management, portal administration, forecasting support, and FBAR preparation. Coordinate day-to-day execution for intercompany funding, settlements, investment operations, letters of credit, guarantees, treasury close, and related accounting handoffs. Automate and scale treasury workflows for request intake, approvals, payment tracking, bank account changes, KYC follow-up, access reviews, evidence collection, and issue resolution. Identify recurring processes, manual pain points, duplicate work, control

About the Team OpenAI’s Forward Deployed Engineering (FDE) team turns research breakthroughs into production-grade systems. We embed deeply with customers to solve high-leverage problems and act as the delivery engine for our most complex large-scale engagements. We move quickly from prototype to production and surface reusable patterns that shape our platform. We operate at the intersection of deployment and development – working closely with OpenAI Research, Product and Partnerships. About the Role As a Technical Deployment Lead (TDL), you will define how OpenAI delivers complex systems to Semiconductor customers. You will own how solutions are scoped, built, shipped, and adopted across high-value engineering workflows such as RTL design, verification, and physical implementation. You’ll translate business outcomes into a technical plan, run day-to-day execution across FDEs, Researchers, and Customer Engineers, and partner with customer teams to ensure delivery supports their goals. You will focus on the semiconductor vertical to deploy next-generation AI capabilities. You will own delivery end-to-end: embedding with customers to map workflows and success criteria, ensuring components ship on time, and leading readiness and change management for adoption. You’ll track progress, manage dependencies, make sequencing decisions, and drive 0→1 prototypes through MVP and scale. You will also share field insights with Product and Research to guide roadmap and priorities. Success will be measured first and foremost by impact - deployments that deliver measurable value against customer goals, drive adoption, and become critical to their workflows. Additional measures of success include delivery reliability (milestones hit, low reopen/churn), operating leverage (patterns reused across deployments), judgment under pressure, and product impact (field signal that shifts roadmaps/architectures). This is a high-trust, high-autonomy role. Success requires deep technical project m

About the Team OpenAI's Industrial Compute organization is building the world's most advanced AI infrastructure ecosystem. Working alongside our cloud partners, infrastructure providers, and internal engineering teams, we operate hyperscale AI campuses that support the training and deployment of frontier AI models. The Site Operations team serves as OpenAI's on-site operational presence, helping ensure campuses operate safely, efficiently, and in alignment with Industrial Compute standards. We work closely with Hardware Operations, Infrastructure Delivery, Network Operations, Security, Facilities, Construction, and our infrastructure partners to support day-to-day site execution and maintain operational readiness. As Industrial Compute continues to expand globally, Site Operations plays a critical role in ensuring each campus is prepared to support reliable AI infrastructure at scale. About the Role We are seeking a Site Operations Technician to support the daily operation of Industrial Compute campuses. This role acts as OpenAI's on-site technical representative, helping coordinate activities across hardware operations, facilities, construction, logistics, security, and external service providers. You will perform routine site inspections, support asset tracking, coordinate vendor activities, assist with operational readiness, document site conditions, and help ensure infrastructure issues are identified and resolved quickly. The ideal candidate enjoys working in highly technical environments, is detail-oriented, and thrives in fast-paced operational settings where no two days are the same. Key Responsibilities Perform routine walkthroughs of Industrial Compute facilities to verify operational readiness and identify potential issues. Monitor site conditions and report abnormalities involving hardware spaces, network rooms, utilities, logistics areas, and common infrastructure. Support coordination of vendors, contractors, and partner organizations performing work o

About the Team The compute infrastructure team runs the GPU fleet and large-scale compute clusters that serve the models backing ChatGPT and the API, while also supporting training workloads for our next generation models. We operate a large, modern GPU fleet and provide a unified platform for other OpenAI teams to seamlessly run production Applied AI and Research training workloads. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role You will be part of an engineer-first TPM team as a Technical Program Manager for Compute Infrastructure who owns the end-to-end delivery of large-scale GPU clusters, partnering with engineers to bring clusters online across external providers and partners. You’ll run a broad, parallel portfolio spanning hardware, networking, power, and cooling—driving execution, risk management, and crisp alignment from working teams through leadership to deliver production-ready capacity at scale. 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: Lead end-to-end delivery of both New Compute SKUs and large-scale GPU clusters across an external partner ecosystem while supporting capacity planning for training and inference. Ability to contextually drive multi-threaded bring-up programs spanning hardware, networking, power, and cooling—owning plans, dependencies, and critical paths. Interface with chip providers to derisk long-term onboarding to new hardware platforms by working across kernels, comms, hardware, and scheduling engineering teams. Build and operationalize program mechanisms (roadmaps, milestones, risk registers, runbooks) that make delivery predictable at massive scale. Partner with engineering to improve cluster turn-up reliability, repeatability, and automation

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

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