High Speed Ai Interconnect Signal Integrity Engineer in San Francisco

About the Team OpenAI’s Legal team plays a crucial role in advancing our mission by tackling novel and consequential legal issues in AI. The commercial infrastructure legal team supports the systems and facilities that make advanced AI possible, including compute, first-party silicon, colocation, and first-party data center development. About the Role We’re seeking a senior commercial infrastructure lawyer to lead legal work across our rapidly growing data center development and colocation portfolio. You will advise on complex, high-value transactions involving new data center sites, power, construction, colocation, and related infrastructure arrangements. This role is designed for a lawyer who understands how data centers are developed and operated—not a general real estate practitioner. You will work closely with infrastructure, finance, procurement, and operations teams, while coordinating outside counsel where appropriate, to help projects move quickly and responsibly. San Francisco is preferred, and occasional travel may be required. In this role, you will: Lead commercial legal strategy and risk management for data center development and colocation transactions. Draft, negotiate, and advise on colocation agreements, construction agreements, power-related arrangements, and other contracts supporting data center development. Support first-party projects involving raw land, site and power rights, design and construction, EPC models, third-party build-to-suit structures, and leasebacks. Partner cross-functionally with infrastructure, finance, procurement, operations, and other stakeholders on fast-moving, complex projects. Manage and collaborate effectively with outside counsel across a high volume of infrastructure matters. Develop scalable legal playbooks and contracting approaches for a growing portfolio of data center sites. You might thrive in this role if you have: 12+ years of legal experience, primarily in commercial legal roles. Deep, hands-on experience

About the Team OpenAI’s mission is to ensure that artificial general intelligence benefits all of humanity. Customer Education plays an important role in that mission by helping people and organizations use increasingly capable AI systems effectively, responsibly, and with confidence. We help customers build the confidence and practical skills to use OpenAI effectively, change how work gets done, and realize lasting value. About the Role Helping organizations adopt AI takes more than access to powerful technology. People across the workforce need the skills and confidence to use it well. Within Customer Education, you will lead the enterprise learning program and team. You will set direction, develop the team, and build a clear, high-quality learning portfolio that moves customers from first learning to confident use and meaningful business impact. This is a rare opportunity to define how customers learn with OpenAI at global scale, alongside the teams shaping the technology. In this role, you will: Lead and develop a high-performing Customer Learning team. Own the customer-facing Learn experience, curriculum, and program portfolio—from strategy through results. Turn priority customer needs into role-based tracks, paths, and high-quality programs. Make the portfolio easy to understand, with clear starting points, progression, and relationships among experiences. Lead how learning reaches customers through owned and partner channels. Use customer and product evidence to measure impact and decide what to build, scale, improve, defer, or stop. You might thrive in this role if you: Build strong teams, grow talent, and create accountability. Shape education strategy from customer needs and turn it into programs with measurable impact. Make clear portfolio choices about investment, capacity, and focus. Turn complex learning into clear journeys customers can understand and use. Reach customers through owned and partner channels, building trust across teams. Qualifications

About the Team The Finance & Supply Chain Engineering organization includes two complementary teams. Software Engineering builds internal full-stack applications, durable agentic workflows, plugins, MCPs, and measurable AI-enabled engineering practices. Data Engineering builds trusted analytics data assets for Finance and Supply Chain. The teams have distinct charters, with important shared dependencies and broad cross team partnerships across Engineering, Applications, Finance, and Supply Chain. About the Role We are looking for a hands-on senior technical leader who will report alongside the Software Engineering and Data Engineering managers. This is an individual-contributor role with no immediate people-management responsibility. The Tech Lead will raise the technical bar across both teams, participate in important cross-team or high-risk design decisions, and directly own and ship high-impact work. The role should improve team judgment and autonomy rather than act as a floating architect or universal approval gate. In this role, you will: Partner with the Software Engineering and Data Engineering managers as a peer technical leader; managers retain accountability for people, staffing, priorities, performance, and delivery commitments. Directly own the architecture, implementation, launch, and operation of one or more high-impact initiatives, remaining accountable for real outcomes rather than advisory output alone. Guide important design decisions that are cross-team, difficult to reverse, or material to security, financial controls, reliability, data quality, or long-term cost of ownership. Establish pragmatic engineering standards across architecture, APIs and data contracts, testing, security, reliability, observability, lineage, data quality, and operational ownership. Advance engineering standards for building with AI, including agentic workflows, evaluation, telemetry, adoption, and outcome measurement. Work across backend, full-stack, data, and big-d

About the role We are building a higher education researcher motion that helps funded labs adopt OpenAI across core research workflows. This role will develop relationships with principal investigators, researchers, research software engineers, research computing teams, and university technology leaders, then translate high-value use cases into sustained Pro, Codex, API, and ChatGPT Edu usage. This is a hybrid business development and program management role. You will identify and qualify priority labs, design phased access and fellows programs, run pilots, remove technical and institutional blockers, and create repeatable paths from individual researchers to lab- and institution-level adoption. Additionally, this role will launch and manage a community of researchers with events, communications and support. In this role, you will: Build a pipeline of funded labs, research centers, and technical champions at priority R1 universities; qualify opportunities based on workflow value, funding path, influence, and expansion potential. Run discovery with researchers and university stakeholders to understand workflows, data and security needs, procurement constraints, and success criteria. Design and operate phased access and fellows programs, including eligibility, selection, offer mechanics, onboarding, office hours, community programming, and pilot goals. Translate research workflows into effective use of Pro, Codex, API, and ChatGPT Edu in partnership with Solutions, Product, and Education account teams. Manage pilots end to end, remove trust, funding, and technical blockers, and drive measurable activation, retention, and expansion. Turn early usage into product feedback, workflow documentation, peer proof, case studies, and repeatable enablement. Build clear handoffs and expansion paths from researcher to lab to institution; track fellow selection, activation, retained usage, workflow proof, conversion, and expansion. You might thrive in this role if you: Relevant exp

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 end-to-end flow of commercial transactions from order intake and provisioning through billing, collections, credit risk, accounts receivable operations, and cash application. The team focuses on accuracy, compliance, operational discipline, and a high-quality customer experience. About the Role We are hiring for the Senior Credit & Collections role to support OpenAI's global receivables operations, with a focus on white-glove support for premier and strategic accounts across the U.S. and key regional areas of AR work, including standard operating procedures, payment methods, customer portals, disputes, cash application handoffs, escalations, and emerging go-to-market channels. In this role, you will manage complex customer accounts, guide priority AR workstreams, support credit reviews, and partner cross-functionally with Sales, Customer Success, Billing Operations, Deal Desk, Legal, Accounting, Cash Application, Finance Systems, and external partners. You will help improve cash collections, reduce aging, support responsible credit decisions, and maintain a strong customer experience across sensitive, high-value, and operationally complex relationships. 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 a portfolio of premier, strategic, and high-touch customer accounts across the U.S. and key regional AR work areas, ensuring timely collections, clear communication, and a white-glove customer experience. Support collections coverage across key regional areas of AR work, including payment follow-up, documentation requirements, portal submission workflows, tax or invoicing considerations, dispute coordination, and escalation management. Support new channel success, including marke

About the Team The Ads Support Delivery team is responsible for helping successfully operate and grow on our Ads product. This includes technical guidance, troubleshooting complex delivery and monetization issues, and partnering closely with Product, Engineering, Trust & Safety and Go-To-Market teams to resolve customer-impacting problems and improve the platform over time. The team’s mission is to deliver a high-quality customer experience at scale by combining strong human support with automation, self-service, and AI-enabled workflows, while maintaining high operational rigor. About the Role: As a Support Delivery Lead for Ads, you will lead a team responsible for end-to-end support delivery across the ads ecosystem, including campaign setup, delivery, billing, measurement, and policy navigation. You will set the operational bar for quality, responsiveness, and consistency; coach and grow the team; and translate support signals into actionable improvements with Engineering, Product, and Go-To-Market partners. 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 and support a team of Ads support engineers, ensuring they have the tools, clarity, and coaching needed to operate at a high bar in a technically complex domain. Set clear expectations and operating standards, run recurring performance reviews, and build development plans that grow both technical depth (ad tech fluency) and customer-facing excellence. Design and continuously improve support coverage for ad buyers, ensuring the team can diagnose delivery issues and monetization and integration issues with equal rigor. Act as the bridge between Support Delivery, Engineering, Product, and Go-To-Market teams. Drive alignment on priorities, escalation paths, launch readiness, tooling improvements and mechanisms to reduce repeated customer pain points. Partner with engineering teams

About the Team The Privacy Engineering team builds secure, reliable systems that help OpenAI meet its legal obligations while protecting user data. We partner closely with Legal and Engineering teams across OpenAI to support lawful data access requests and other critical legal workflows. Our work turns complex, high-stakes processes into auditable and dependable technical systems with clear human oversight and strong privacy and security controls. About the Role We’re looking for a full-stack Software Engineer to build the internal tools and data pipelines that power lawful data access request workflows and Legal Operations. You will work across product and data systems to make authorized retrieval and case handling accurate, efficient, and auditable. This role is well suited to someone who enjoys translating ambiguous operational requirements into durable systems, cares deeply about sensitive-data handling, and wants to improve both technical reliability and the day-to-day experience of the people operating these workflows. This role is based in San Francisco, CA, with two additional locations under consideration: London, UK, and Dublin, Ireland. 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: Design, build, and operate backend systems and workflow tooling for the full lifecycle of lawful data access requests, from intake and scoping through authorized retrieval, review, preparation, and audit. Build reliable data pipelines and interfaces across products and data stores so authorized teams can locate and handle the right records accurately and reproducibly. Implement least-privilege access, approval gates, provenance, audit trails, data minimization, and safe failure modes for sensitive workflows. Partner with Legal and Legal Operations to translate legal and operational requirements into clear technical designs and intuitive operator experiences. Identify responsible automation o

About the Team OpenAI's research training infrastructure powers how our frontier models are trained and evaluated. The Simulation team sits at the intersection between the agentic harness that powers OpenAI's products and the research infrastructure where GPT-next is trained, ensuring that our model's training environment is as realistic as possible. This team owns the integration layer that connects our production harness capabilities into the training stack. The work is highly cross-functional and high leverage: researchers depend on it to run experiments and evaluations reliably as well as to develop the next generation of harness capabilities. Failures in this surface can materially affect training velocity and correctness. About the Role We're looking for a Principal Software Engineer to lead the architecture and evolution of the Simulation Platform. You'll own a critical interface between research and engineering, building the systems, APIs, and operational patterns that let researchers use agentic coding infrastructure safely and effectively in training environments. This role is ideal for a senior backend or infrastructure engineer with strong technical judgment, product sense for highly technical users, and the ability to drive execution across multiple teams. The highest-leverage work is building robust infrastructure that supports and accelerates research without compromising engineering quality. In this role, you will Design, build, and evolve the integration between the Codex harness that powers OpenAI's products and research training infrastructure used for training GPT-next Build a platform for our LLMs to train and be evaluated in simulated environments that mimic their deployment setting as closely as possible, on every axis: agentic harness, compute substrate, timing, tools, data sources, humans in the loop, and more Own major integration surfaces end-to-end, from architecture and API design through rollout, operations, and long-term maintenance Bu

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 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 The Pricing & Monetization team is responsible for how our products create and capture value. We partner closely with Product, Engineering, Data Science, GTM, and Finance to design pricing models, packaging, and commercial strategies that support adoption, growth, and long-term scaling of the business. To thrive in this team, you need to be a proactive problem-solver who excels at bringing structure to ambiguous challenges. Our work demands strategic thinking, cross-functional collaboration, and precision in execution. Team members succeed when they are analytical, detail-oriented, skilled at balancing multiple priorities, and passionate about driving high-stakes projects forward to deliver meaningful results. About the Role We are looking for a Pricing Strategist to shape how we price and monetize OpenAI’s API platform. You’ll own the end-to-end pricing strategy across model launches, price architecture, packaging, commitments and discounts, and monetization guardrails. You’ll work closely with senior leaders across Product, Engineering, Data Science, GTM, and Finance to define pricing approaches, improve commercial decision-making, and bring more rigor to how we monetize our API offerings. You should be comfortable building monetization frameworks and commercial policies, analyzing tradeoffs, supporting high-impact decisions and driving decision making. You should also care deeply about the customer perspective and believe that strong pricing reflects a real understanding of customer value, needs, and friction points in order to build pricing that is clear, fair, and aligned with how customers experience our products. This role will report to the Head of Product Pricing for API & Platform. What you’ll do Develop the end-to-end pricing strategy for our API platform, including model launch pricing, price architecture, packaging, discount logic, and monetization guardrails. Recommend pricing for new models, capabilities, and platform offerings,

About the Team OpenAI’s Infrastructure Operations team is responsible for the availability, reliability, and operational excellence of one of the world’s largest AI infrastructure networks. The team owns day-to-day operations of production AI networks across Industrial Compute's data centers, working with colocation providers, deployment teams, and hardware vendors to deliver highly available GPU infrastructure for AI training and inference workloads. About the Role We are seeking an Infrastructure Operations Engineer to operate and improve the large-scale Ethernet fabrics that support GPU clusters, storage systems, and management infrastructure. This role combines hands-on production operations with automation, observability, and incident response across a global AI network. The ideal candidate has experience operating high-availability data center, cloud, AI, or HPC networks and can move comfortably from physical-layer troubleshooting to routing and fabric behavior, change execution, and root-cause analysis. You will partner closely with network architecture, systems engineering, GPU engineering, storage engineering, security, deployment, site operations, service providers, colocation partners, and hardware vendors to raise reliability and reduce operational toil. Key Responsibilities Own the operational health, availability, and reliability of production AI network infrastructure across Industrial Compute's data centers. Monitor, troubleshoot, and resolve network incidents while meeting service-level objectives (SLOs), reducing Mean Time to Detect (MTTD), and minimizing Mean Time to Recovery (MTTR). Operate and maintain large-scale Ethernet fabrics supporting GPU compute, storage, and management networks. Execute production network changes, maintenance windows, and capacity expansions with minimal customer impact. Manage the hardware lifecycle, including switch and optics replacements, RMA coordination, software upgrades, and preventive maintenance. Support new A

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 Data Platform at OpenAI owns the foundational data stack powering critical product, research, and analytics workflows. We operate some of the largest Spark compute fleets in production; design, and build data lakes and metadata systems on Iceberg and Delta with a vision toward exabyte-scale architecture; run high throughput streaming platforms on Kafka and Flink; provide orchestration with Airflow; and support ML feature engineering tooling such as Chronon. Our mission is to deliver reliable, secure, and efficient data access at scale and accelerate intelligent, AI assisted data workflows. Join us to build and operate these core platforms that underpin OpenAI products, research, and analytics. We’re not just scaling infrastructure – we’re redefining how people interact with data. Our vision includes intelligent interfaces and AI-assisted workflows that make working with data faster, more reliable, and more intuitive. About the Role This role focuses on building and operating data infrastructure that supports massive compute fleets and storage systems, designed for high performance and scalability. You’ll help design, build, and operate the next generation of data infrastructure at OpenAI. You will scale and harden big data compute and storage platforms, build and support high-throughput streaming systems, build and operate low latency data ingestions, enable secure and governed data access for ML and analytics, and design for reliability and performance at extreme scale. You will take full lifecycle ownership: architecture, implementation, production operations, and on-call participation. You’ve supported Spark, Kafka, Flink, Airflow, Trino, or Iceberg as platforms. You’re well-versed in infrastructure tooling like Terraform, experienced in debugging large-scale distributed systems, and excited about solving data infrastructure problems in the AI space. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per wee

By applying to this role, you will be considered for Research Engineer roles across all teams at OpenAI. About the Role As a Research Engineer here, you will be responsible for building AI systems that can perform previously impossible tasks or achieve unprecedented levels of performance. We're looking for people with solid engineering skills (for example designing, implementing, and improving a massive-scale distributed machine learning system), writing bug-free machine learning code, and building the science behind the algorithms employed. The most outstanding deep learning results are increasingly attained at a massive scale, and these results require engineers who are comfortable working in large distributed systems. We expect engineering to play a key role in most major advances in AI of the future. We expect you to: Have strong programming skills Have experience working in large distributed systems Be excited about OpenAI’s approach to research Nice to have: Interested in and thoughtful about the impacts of AI technology Past experience in creating high-performance implementations of deep learning algorithms About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment