Executive Business Partner Jobs

About the 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 the Role We're looking for an experienced Electrical Engineer to help develop the next generation of robotic systems at OpenAI. This role spans the full lifecycle of hardware development, from early concept exploration and prototyping through circuit design, component selection, PCB layout, bring-up, integration, and deployment. Engineers in this role are expected to independently drive significant hardware efforts from initial concept through deployment. You will translate ambiguous goals into concrete engineering plans, make key technical decisions, coordinate closely with cross-functional partners, and own execution through the iterations required to deliver a successful system. Many of the systems we build are still being defined. You will work closely with mechanical, firmware, software, controls, and research teams to evaluate new ideas, develop novel hardware, and integrate it into robotic platforms. Success in this role requires strong engineering judgment, comfort operating in ambiguous spaces, and the ability to balance rapid experimentation with the discipline required to build reliable and scalable systems. The ideal candidate enjoys building things from first principles and is equally comfortable evaluating a new technology, debugging a prototype on the bench, reviewing PCB layout details, and driving system integration efforts. You should be able to move quickly when appropriate, but also know when investing in robustness, simplicity, or infrastructure will create leverage for future development. This role is

About the Team The Systems Integration team is responsible for building the infrastructure, tooling, and validation systems that ensure our device software is reliable, testable, and ready to ship. We design and maintain automated test frameworks, hardware-in-the-loop labs, and release pipelines that keep quality signals trustworthy and enable rapid, safe product launches. Our work spans developer tools, automation, systems integration, and cross-team collaboration to ensure every release meets the highest standards. About the Role As a Software Engineer, Quality and Developer Tools , you will build and own the systems that validate our device software—from test frameworks and regression infrastructure to hardware-in-the-loop labs and release gates. You’ll design the tooling and automation that keep quality signals trustworthy, integrate them into CI/CD, and make it easy for engineers and QA vendor technicians to execute reliable, repeatable workflows. We’re looking for engineers with deep experience in software quality, automation, developer tooling, and hardware-software integration who thrive on building scalable, reliable systems for validation and release readiness. This role is based in San Francisco, CA. We use a hybrid work model of four days in the office per week and offer relocation assistance to new employees. In this role, you will: Test infrastructure & frameworks: Design, implement, and maintain a unified test framework for device software across unit, integration, system, and end-to-end testing, with reproducible runs and integrations with GitHub, Linear, and Slack. CI/CD integration & releases: Integrate test suites with Buildkite, enforce promotion criteria for staging and production, auto-file regressions, and publish traceable artifacts and release notes. Hardware-in-the-loop lab design & orchestration: Plan and bring up racks, power and networking systems, and orchestration for device testing; support automated flashing, provisioning

Job Description: Data Scientist, B2B Demand Generation, Growth & Measurement About the Role We are hiring a Data Scientist to lead measurement, experimentation, and decision science for B2B marketing demand generation. You will help us understand which marketing investments create incremental demand, qualified pipeline, and revenue and how to scale them efficiently. Our mandate is to build a rigorous, full-funnel view of how B2B marketing creates demand and moves prospects from awareness and engagement to qualified opportunities, closed-won revenue, and expansion. You will shape how we measure marketing impact and influence across channels, campaigns, audiences, and account segments. In this role, you will partner closely with B2B Marketing, Demand Generation, Growth, Sales, RevOps, Finance to connect marketing activity to qualified pipeline, customer acquisition, and efficient revenue growth. What You’ll Do Define north-star, leading, and guardrail metrics for B2B demand generation, including account engagement, qualified leads and opportunities, sourced and influenced pipeline, conversion rates, pipeline velocity, and incremental ARR. Design and execute measurement and experimentation strategies across channels and campaigns, using randomized tests, audience or geographic holdouts, lift studies, quasi-experimental methods, and other causal approaches suited to long B2B sales cycles. Analyze channel, audience, campaign, creative, content, landing-page, and account-segment performance to identify the drivers of qualified demand, funnel conversion, pipeline quality, and incremental revenue. Partner with Marketing, Sales, RevOps, Finance, Product, and Engineering to improve instrumentation, campaign taxonomy, CRM data quality, lead-to-account matching, and the operating cadence for acting on measurement insights. Build AI-native measurement and decision-support workflows, using LLMs and agents to synthesize campaign performance, surface growth opportunities, and h

About the Team At OpenAI, our Trust, Safety & Risk Operations teams safeguard our products, users, and the company from abuse, fraud, scams, regulatory non-compliance, and other emerging risks. We operate at the intersection of operations, compliance, user trust, and safety working closely with Legal, Policy, Engineering, Product, Go-To-Market, and external partners to ensure our platforms are safe, compliant, and trusted by a diverse, global user base. The Global Safety Response Operations team provides 24/7 coverage for user safety, risk, and regulatory escalations across OpenAI’s products, handling the highest-priority cases that require human judgment and rapid response. The team operates as the core escalation and delivery arm of OpenAI’s safety operations, ensuring that our products remain safe and aligned with policy while enabling timely, empathetic, and consistent user support. About the Role The Global Safety Response Operations Lead is a hands-on team lead who both manages a regional Safety Response team and personally handles high-risk safety cases. This role combines frontline safety work with people leadership, operational ownership, and cross-functional coordination. You will lead a team of Safety Response Analysts who handle OpenAI’s most sensitive and high-impact cases, while also personally contributing to casework for complex, high-risk, or high-visibility issues. You will own the execution of high severity escalations in your region and ensure proper execution and communication to cross functional stakeholders You will be accountable for ensuring your region consistently meets utilization, quality, and SLA targets while serving as the operational interface with Product, Policy, Legal, Investigations, and regional stakeholders. This is a 24/7 global operation that requires flexibility to support rotating shifts, including nights, weekends, and holidays, as part of a leadership on-call model. In This Role, You Will: Lead and coach a regional te

About the Team We are a small and fast-moving partnerships team that shapes and executes OpenAI’s most strategic collaborations in India. We work at the intersection of product, growth, and market expansion to build impactful relationships that accelerate adoption and unlock new use cases for OpenAI’s technologies. The team partners closely with product, engineering, research, marketing, finance, legal, and operations to design and deliver partnerships that scale OpenAI’s presence and relevance across diverse markets. Our focus is on establishing long-term strategic partners and driving sustainable growth through integrated, high-impact product experiences across consumer and B2B offerings in the region. About the Role As India Product Partnerships Lead, you will lead and scale strategic partnerships primarily in India. You will be responsible for initiating, structuring, and growing partnerships that expand OpenAI’s distribution, deepen user engagement, and accelerate product adoption across the region. This role requires strong commercial judgment, regional market fluency, and the ability to work closely with product teams to translate strategic opportunities into scalable partnership models. You will operate at both strategic and execution levels — shaping partnership strategy while driving concrete outcomes that contribute to OpenAI’s growth. This role is based in Mumbai. You’ll be responsible for: Initiating and scaling strategic partnerships in India that drive user growth, distribution, and adoption for OpenAI’s consumer and B2B offerings. Establishing and managing long-term strategic partners in India, serving as the primary relationship owner and strategic lead. Identifying and executing market-specific growth opportunities such as bundled offerings, embedded distribution, platform integrations, and co-developed product experiences. Shaping joint product strategy with partners by aligning roadmaps, defining shared priorities, and unlocking new use cases tai

About the Team The Human Data team at OpenAI is responsible for identifying and mitigating risks in advanced AI systems by designing evaluations, surfacing vulnerabilities, and collaborating closely with researchers to strengthen model reliability and public trust. About the Role As a Research Program Manager, you will lead initiatives that test the safety and robustness of OpenAI’s models through creative experimentation and structured evaluation. You’ll coordinate efforts across research and engineering teams to transform ambiguous risks into concrete research programs and influence future model development and deployment. We’re looking for people who are technically savvy, comfortable with ambiguity, and excited about shaping the future of safe AI. 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 programs that explore unexpected model behaviors and identify failure modes. Translate vague or emergent risk signals into clear priorities and actionable research plans. Design and run creative evaluations, experiments, and red-teaming campaigns. Collaborate with research, product, and deployment teams to integrate findings into model training and deployment cycles. Develop repeatable systems for tracking model performance and understanding emerging behavior patterns. You might thrive in this role if you: Have strong experience in technical program management, with excellent organizational and communication skills. Are familiar with large language models, prompt engineering, or model evaluation techniques. Are comfortable managing fast-paced, high-uncertainty projects and shaping them from the ground up. Are creative and resourceful in devising new methods for testing model behavior and performance. Can effectively coordinate across technical and non-technical stakeholders to drive alignment and execution. About OpenAI OpenAI is an AI resear

About the team OpenAI’s Forward Deployed Engineering (FDE) team partners with global pharma and biotech, CROs, and research institutions to deploy production-grade AI systems across the R&D value chain. We operate at the intersection of customer delivery and core platform development, converting early deployments into repeatable system standards and evaluation practices that scale across regulated environments. About the role As a Life Sciences FDE Manager, you’ll lead a team of FDEs delivering production AI systems across drug discovery and development workflows. You’ll own delivery outcomes and team leverage while staying hands-on as a player-coach. This includes building and shipping alongside the team, setting technical direction, and maintaining a high bar for production-grade systems in regulated environments. We measure success through the health and quality of your FDE team, production adoption and measurable workflow impact, the quality of eval-driven feedback delivered back to Product and Research, and the repeatability of deployment patterns across life sciences customers. This role is based in New York City We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. This role will require travel up to 25%. In this role you will Lead and grow a team of FDEs delivering production AI systems across regulated life sciences environments Be accountable for your team’s end-to-end delivery outcomes, balancing scope, speed, robustness, and risk in high-stakes deployments Coach and develop engineers through direct feedback, high technical standards, and clear expectations for execution and ownership Operate as a player-coach, directly contributing to production systems while leading, coaching, and setting technical direction Guide teams through ambiguous, multi-workstream engagements spanning data, workflows, infrastructure, security, and scientific stakeholders Run evaluation loops that measure model and system quality against

About the Team The Consumer Products team at OpenAI builds the hardware that brings advanced AI technology directly into people’s hands. We design, engineer, and manufacture next-generation consumer devices that combine elegant design, robust engineering, and cutting-edge AI. Our team spans mechanical, electrical, and systems engineering — partnering closely with industrial design, operations, and software to create seamless, high-quality experiences that make AI more accessible and useful. About the Role As a Hardware Engineer on the Consumer Products team, you’ll contribute to the design, development, and integration of complex hardware systems for new AI-driven devices. You’ll work across disciplines to translate early product concepts into reliable, scalable, and beautifully crafted products ready for mass production. This role is based in Singapore. We follow a hybrid model (four days per week in the office) and offer relocation support for new employees. Occasional travel to manufacturing partners may be required. In this role, you will: Design, prototype, and validate mechanical and electrical subsystems from early development through mass production. Collaborate closely with design, operations, and manufacturing teams to ensure quality, reliability, and scalability. Drive DFM/DFA reviews, design iterations, and bring-up of prototype and pilot builds. Debug complex system-level issues and lead root-cause investigations and resolutions. Partner with global suppliers and cross-functional teams to ensure flawless execution from concept to launch. You might thrive in this role if you: Have 6+ years of experience in consumer hardware, consumer electronics, or advanced product development. Bring deep technical fluency in mechanical, electrical, or systems engineering (cross-disciplinary experience a plus). Have taken at least one consumer product from concept to mass production. Are energized by hands-on problem solving, iteration, and building in fast-paced enviro

About the Team Training Runtime designs the core distributed runtime that powers everything from early research experiments to frontier-scale model runs. We work on building robust, scalable, high performance components to support our distributed training workloads. Our priorities are to maximize the productivity of our researchers and our hardware, with the goal of accelerating progress towards AGI. Within Training Runtime, the Process Management team develops the distributed OS responsible for launching, coordinating, and supervising the large numbers of processes that make up modern training workloads. Our runtime sits beneath training frameworks and on top of research infrastructure, ensuring jobs run reliably across massive clusters while maintaining performance, stability, and observability. Success for us is measured by both system reliability and researcher velocity - enabling ideas to scale from experiments to production training runs. About the Role As a Training Runtime: Process Management Engineer , you will work on the software that ties thousands of computers together and exposes them as a unified system. This system has to serve individual researchers running multiple parallel experiments, as well as our largest training runs spanning 100’s of thousands and even millions of machines and accelerators. This requires easy to use, introspectable systems that can promote a fast debugging and development cycle, as well as relentless optimization for scale while maintaining stability and performance throughout. You will work primarily in Rust , building high-performance asynchronous systems with a strong emphasis on performance, correctness, and scalability. Working at this scale and at the frontier of AI development poses novel challenges. Out-of-the-box approaches often don’t work. The problems you will be working on are highly ambiguous and require strong design judgment as well as proficient execution to advance the state of our infrastructure. We’re loo

About the Team The Platform Analytics team builds the systems OpenAI researchers use to understand the quality and behavior of the models we train including what models are doing, why they behave in a particular way, and how that behavior changes across experiments. Neptune is a core part of this work. It ingests, stores, queries, and visualizes large volumes of metrics from pretraining, post-training, and reinforcement learning. Hundreds of researchers depend on these systems in their daily work to compare experiments, debug unexpected behavior, and decide what to try next. Our scope is broader than metrics. We also build platforms that help researchers analyze samples, traces, evaluation results, and other structured or unstructured data through dashboards, APIs, and increasingly agent-driven workflows. These systems need to remain fast, reliable, and understandable as the scale and complexity of research change quickly. We are not trying to become a consulting team that builds a separate solution for every research project. We work directly with researchers to understand recurring problems, then turn them into reusable infrastructure and platform capabilities that many teams can build on. About the Role We’re looking for a hands-on experienced software engineer who can take ownership of a critical system and drive it from problem definition through production adoption. This person should be able to own a platform such as CacheHouse end to end: define its technical direction, design its data model and storage architecture, integrate it with several research dashboards and workflows, guide one or two engineers, and ensure the system works reliably for its users. The right candidate should already bring the technical judgment, ownership, and execution expected at this level. The primary learning curve should be OpenAI’s stack and research problem space, not learning how to lead a complex engineering effort or deliver a production system. You will work directly with

About the Team The Agent Enablement team works across engineering, product, design, and research to bring our technology to the world. We seek to learn from deployment and broadly distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. We aim to make our innovative tools globally accessible, transcending geographic, economic, and platform barriers. Our commitment is to facilitate the use of AI to enhance lives, supported by rigorous insights into how people use our products. About the Role We are looking for experienced full-stack engineers to join our new Agent Enablement team. Our goal is to design and grow an open ecosystem of agent-enabled sites and services. This is a wide-ranging role: you’ll build new user and agent identity protocols, user experiences to control and observe agents across web, desktop, and mobile, and much more. We will rely on you to drive our technical decisions while also steering our product and partnership direction, optimizing for both short-term impact and long-term success of the ecosystem. We value engineers who are impact-driven, autonomous, and adept at removing barriers to forward progress. In this role, you will: Design the primitives and protocols for an open agent ecosystem, enabling our users’ agents to make the best use of sites and services across the internet. Build a next-generation user experience to observe and control agents, across web, desktop, and mobile. Evolve our approach to token consumption across subscriptions and API customers. Execute on fast-paced projects in collaboration with research, design, data science and other product engineering teams. Work closely with our strategic customers and partners to grow the ecosystem. You might thrive in this role if you: Have strong full-stack engineering skills and experience shipping customer-facing products from concept to production. You’re comfortable working across frontend, backend, APIs, data models, and product desig

About the Team The Online Data team builds and operates the core online database and indexing services for OpenAI’s production AI applications, including supporting the explosive growth of ChatGPT, the #1 AI app in the world, and Codex, the fastest growing agentic development toolset in the world. Our mission is to ensure the reliability, correctness, and scalability of our online data stack and to curate a comprehensive portfolio of services that matches the relentless ambition of OpenAI, enabling our product and research teams to build 0-100 without getting bogged down in the minutiae of multi-region, multi-cloud, exabyte-scale data infrastructure. About the Role We are seeking an Engineering Manager to lead our Online Data Systems team, responsible for our in-house database and indexing technology. This role is about shepherding a team of world-class engineers tasked with building and operating hyperscale data storage and retrieval technology. You’ll be overseeing the delivery of extremely challenging engineering work in areas like distributed query execution, multi-region federation, self-orchestrating and self-healing services, low-level performance optimization, and more. There are few companies in the world building this kind of technology in-house at this scale where you’ll still be getting in on the ground floor. Instead of being a cog in the machine spending months chasing small optimizations, you’ll play a major part of shaping our future. In this role, you will: Build, lead, and grow high-performing infrastructure engineering teams. Drive the evolution of OpenAI’s in-house online data technologies, our core, hyper-scale database systems, indexing technologies, and vector search. Anchor delivery around measurable reliability goals (SLOs, etc) to ensure system performance and resiliency is above reproach. Champion pragmatic use of agent technology to amplify execution velocity. Reduce operational toil and incident frequency through better abstractions, gua

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 are seeking an experienced Optical Network Engineer to lead Laser related work within our optical interconnect efforts for large-scale compute systems. The role also requires broad, hands-on optical validation experience across IM/DD-based interconnects, working from lab characterization through production readiness and scaled deployment. In this role you will: Drive laser-focused requirements and technical direction within the broader optical interconnect roadmap. Lead evaluation and validation of optical components and subsystems, including laser-based elements, in lab and production-representative environments. Support end-to-end optical testing for IM/DD interconnects (e.g., module/system bring-up, characterization, debug, and readiness for scale). Work with external partners to align on development milestones, performance targets, and quality expectations. Own technical issue triage and resolution across performance, reliability, and manufacturability topics. Collaborate across internal teams to support integration, rollout, and operational success at scale. You might thrive in this role if you have: Strong experience in laser-focused optical engineering (development, validation, manufacturing readiness, or field support). Broad hands-on background with IM/DD optical technologies and optical test/debug workflows. Experience working with external suppliers/manufacturing partners and production-oriented execution. Demonstrated ability to debug complex t

About the Team The Support team is central to ensuring that our customers' experience with our products is nothing short of exceptional. We resolve complex issues, provide technical guidance, and support customers in maximizing value and adoption from deploying our products. We work closely with Sales, Technical Success, Product, Engineering and others to deliver the best possible experience to our customers at scale. OpenAI's customers represent a range of diverse backgrounds and maturity, from early-stage startups to established global enterprises. About the Role As a Product Engagement Manager on the User Operations team, you will lead a team of Product Engagement Specialists responsible for ensuring smooth, successful product launches across internal and external teams. You’ll be the glue connecting product teams and support operations, equipping teams with the tools and knowledge needed to support new product rollouts. You’ll build scalable feedback loops that capture the voice of the user and translate insights into actionable product improvements, and ensure that frontline teams have the knowledge and skills to deliver accurate, delightful customer interactions at scale. We’re looking for someone who thrives at the intersection of product management, team enablement, and customer advocacy, and who enjoys working cross-functionally in a fast-paced, evolving environment. This person will manage the day-to-day work while also helping architect the systems needed to scale it. The successful candidate will be a leader-coach who can lead a small team while continuing to perform individual contributor work. 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 a team coordinating product launches across internal and external teams, ensuring seamless execution and support readiness. Set the team’s strategy and priorities, translate them into c

About the Team The Future of Computing Research team is an applied research team in the Consumer Devices group focused on developing new methods and models to support our vision as we advance forward in our mission of building AGI that benefits all of humanity. About the Role As a Technical Lead on the Future of Computing Research team, you will work together with both the best ML researchers in the world and the greatest design talent of our generation to push the frontier of model capabilities. This role is based in San Francisco, CA. We follow a hybrid model with 3 days a week in the office and offer relocation assistance to new employees. In this role, you will: Evaluate and select silicon platforms (GPUs, NPUs, and specialized accelerators) for on-device and edge deployment of OpenAI models. Work closely with research teams to co-design model architectures that meet real-world deployment constraints such as latency, memory, power, and bandwidth. Analyze and model system performance, identifying tradeoffs between model design, memory hierarchy, compute throughput, and hardware capabilities. Partner with hardware vendors and internal infrastructure teams to bring up new accelerators and ensure efficient execution of transformer workloads. Build and lead a team of engineers responsible for implementing the low-level inference stack, including kernel development and runtime systems. Run through the necessary walls to take nascent research capabilities and turn them into capabilities we can build on top of. You might thrive in this role if you: Have experience evaluating or deploying workloads on GPUs, NPUs, or other specialized accelerators. Understand the performance characteristics of transformer models, including attention, KV-cache behavior, and memory bandwidth requirements. Have designed or optimized high-performance compute systems, such as inference engines, distributed runtimes, or hardware-aware ML pipelines. Have experience building or leading teams work