Systems Architect in United States

About the Team OpenAI, in partnership with our capital and technology partners, is building a global network of advanced datacenters to support the most demanding AI workloads. The Industrial Compute team ensures that all datacenter systems are manufactured, delivered, and commissioned to the highest standards of quality, reliability, and performance. We work closely with manufacturing partners, engineering teams, and operations staff to ensure that every component is delivered ready for installation, startup, and long-term service. About the Role We are seeking an experienced Quality Engineer (QE) to drive Product and Site Quality initiatives across OpenAI’s infrastructure ecosystem. In this role, you will establish, implement, and manage a comprehensive, quality-focused program across our global supply chain network, ensuring excellence from design through deployment. You will be responsible for end-to-end quality of finished products, as well as maintaining and elevating manufacturing site quality standards. Working cross-functionally with Design (NPI) and Engineering teams, you will help achieve First Pass Yield (FPY), quality, and reliability targets. This includes leading site and fixture validation efforts, driving yield improvement initiatives (Yield Bridge, CPI), and implementing robust corrective and preventive actions (CAPA) to resolve issues at their root cause. In addition, you will play a key role in supplier quality management, assessing and qualifying new vendors, overseeing ongoing supplier performance, and ensuring readiness for future business awards. You will lead vendor audits, monitor key performance metrics, and coordinate corrective actions to ensure predictable delivery schedules, reduced operational risk, and high system reliability. By partnering closely with external suppliers and internal Engineering and Operations stakeholders, you will help ensure OpenAI’s datacenter infrastructure is delivered on time, meets the highest quality standa

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 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're a growing hardware company. As we scale, we also need a supply chain that evolves and stays nimble to the changing shape and direction our engineers designs. Today we need someone who understands the iterative process of R&D but is also ready to expand into new product introduction (NPI), and after that, high-volume manufacturing. We're hiring for where we're headed, not just where we are today. This role prioritizes judgment, adaptability, and analytical ability over years of experience alone. A strong candidate will be able to reason from first principles, quickly develop expertise in new commodities, and identify potential commercial or technical issues before they affect the program. While extensive tenure is not required, this is not an entry-level position; candidates should have a solid foundation in strategic sourcing, supplier management, and hardware manufacturing. Over time, you'll help us build out a full supply chain organization: buyers, global supply managers (GSMs), contract manufacturing leads, and specialists across categories like precision machining, gears and mechanical components, EMS/PCBA, electrical components, and contract/JDM manufacturing. Where this role goes - into a specific commodity, into people management, into ops - will depend on where you're strongest and where the business needs you most. This role is based in San Francisco, CA and requires in-person presence 4 days a week and up to 30% travel to vendor sites. In this role you will: Partner directly with engineering during R&

About the Team The Workload team is responsible for designing and running OpenAI’s LLM training and inference infrastructure that powers frontier models at massive scale. Our systems unify how researchers train and serve models, abstracting away the complexity of performance, parallelism, and execution across vast GPU/accelerator fleets. By providing this foundation, the Workload team ensures that researchers can focus on advancing model capabilities while we handle the scale, efficiency, and reliability required to bring those models to life. About the Role We are looking for an engineer to design and implement the dataset infrastructure that powers OpenAI’s next-generation training stack. You will be responsible for building standardized dataset interfaces, scaling pipelines across thousands of GPUs, and proactively testing performance bottlenecks. In this role, you will collaborate closely with the multimodal researchers, and other infra groups to ensure datasets are unified, efficient, and easy to consume. In this role, you will: Design and maintain standardized dataset APIs, including for multimodal (MM) data that cannot fit in memory. Build proactive testing and scale validation pipelines for dataset loading at GPU scale. Collaborate with teammates to integrate datasets seamlessly into training and inference pipelines, ensuring smooth adoption and a great user experience. Document and maintain dataset interfaces so they are discoverable, consistent, and easy for other teams to adopt. Establish safeguards and validation systems to ensure datasets remain reproducible and unchanged once standardized. Debug and resolve performance bottlenecks in distributed dataset loading (e.g., straggler systems slowing global training). Provide visualization and inspection tools to surface errors, bugs, or bottlenecks in datasets. You might thrive in this role if you: Have strong engineering fundamentals with experience in distributed systems, data pipelines, or infrastructure.

About the Team OpenAI’s Inference team powers the deployment of our most advanced models - including our GPT models, 4o Image Generation, and Whisper - across a variety of platforms. Our work ensures these models are available, performant, and scalable in production, and we partner closely with Research to bring the next generation of models into the world. We're a small, fast-moving team of engineers focused on delivering a world-class developer experience while pushing the boundaries of what AI can do. We’re expanding into multimodal inference, building the infrastructure needed to serve models that handle image, audio, and other non-text modalities. These workloads are inherently more heterogeneous and experimental, involving diverse model sizes and interactions, more complex input/output formats, and tighter coordination with product and research. About the Role We’re looking for a software engineer to help us serve OpenAI’s multimodal models at scale. You’ll be part of a small team responsible for building reliable, high-performance infrastructure for serving real-time audio, image, and other MM workloads in production. This work is inherently cross-functional: you’ll collaborate directly with researchers training these models and with product teams defining new modalities of interaction. You'll build and optimize the systems that let users generate speech, understand images, and interact with models in ways far beyond text. In this role, you will: Design and implement inference infrastructure for large-scale multimodal models. Optimize systems for high-throughput, low-latency delivery of image and audio inputs and outputs. Enable experimental research workflows to transition into reliable production services. Collaborate closely with researchers, infra teams, and product engineers to deploy state-of-the-art capabilities. Contribute to system-level improvements including GPU utilization, tensor parallelism, and hardware abstraction layers. You might thrive in t

About the Team The Privacy Engineering Team at OpenAI is committed to integrating privacy as a foundational element in OpenAI's mission of advancing Artificial General Intelligence (AGI). Our focus is on all OpenAI products and systems handling user data, striving to uphold the highest standards of data privacy and security. We build essential production services, develop novel privacy-preserving techniques, and equip cross-functional engineering and research partners with the necessary tools to ensure responsible data use. Our approach to prioritizing responsible data use is integral to OpenAI's mission of safely introducing AGI that offers widespread benefits. About the Role As a part of the Privacy Engineering Team, you will work on the frontlines of safeguarding user data while ensuring the usability and efficiency of our AI systems. You will help us understand and implement the latest research in privacy-enhancing technologies such as differential privacy, federated learning, and data memorization. Moreover, you will focus on investigating the interaction between privacy and machine learning, developing innovative techniques to improve data anonymization, and preventing model inversion and membership inference attacks. This position is located in San Francisco. Relocation assistance is available. In this role, you will: Design and prototype privacy-preserving machine-learning algorithms (e.g., differential privacy, secure aggregation, federated learning) that can be deployed at OpenAI scale. Measure and strengthen model robustness against privacy attacks such as membership inference, model inversion, and data memorization leaks—balancing utility with provable guarantees. Develop internal libraries, evaluation suites, and documentation that make cutting-edge privacy techniques accessible to engineering and research teams. Lead deep-dive investigations into the privacy–performance trade-offs of large models, publishing insights that inform model-training and prod

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 OpenAI's Hardware organization builds supercompute platforms from silicon and boards to full rack-scale systems to power advanced AI workloads. This role owns end-to-end quality for high-speed interconnect hardware across the product lifecycle: early design influence, supplier/contract manufacturer readiness, qualification, ramp, and fleet quality in lab and data center environments. You will be the quality lead for advanced interconnect components and assemblies, including high-speed copper cables, cable cartridges, patch panels, backplane/cable-backplane solutions, high-speed connectors, and related electro-mechanical interfaces. You will partner closely with electrical, mechanical, SI/PI, systems, reliability, operations, and external vendors to prevent escapes and drive rapid, data-driven containment and corrective action. In this role you will: Own quality for advanced interconnect components and assemblies: high-speed connectors, high-speed copper cables, cable cartridges (e.g., cable cassette style assemblies), patch panels & optics, and backplane/cable-backplane interconnect solutions. Drive quality-by-design: participate in design reviews, DFM/DFx, tolerance stacks, material and plating selections, connector mating strategy, strain relief, and assembly methods to reduce variation and field failures. Define and track quality and reliability metrics (DPPM, yield, escapes, RMA/FRACAS trends, Cpk/Ppk where applicable) for interconnects across NPI and m

About the Team Business Marketing at OpenAI helps companies understand, adopt, and realize value from intelligence at work. We believe our own marketing organization should demonstrate what changes when intelligence becomes part of the work: fewer manual handoffs, faster learning, better use of customer and product signals, and more capacity for ambitious thinking. Marketing Technology works across Marketing, go-to-market, Data, Engineering, IT, Security, and Product to define the systems, agents, data, workflows, and operating model that power modern marketing at OpenAI. The team has an opportunity to rethink marketing operations alongside the people building the models, products, and infrastructure shaping the future of AI. About the Role We are hiring a Head of Marketing Operations & Technology to build the most AI-enabled marketing operations organization in the world. You will own the systems, infrastructure, data, and workflows that help Marketing operate with greater intelligence, speed, and impact. You will set the function’s strategy, decide what to build or buy, and develop new capabilities where existing solutions fall short. This role sits at the intersection of marketing, technology, data, and AI. You will partner closely with Engineering, Product, Sales, Growth, and Revenue Operations while building a team of technical operators and builders who can turn ambitious ideas into dependable systems. We welcome varied backgrounds—from marketing operations leaders who have expanded the function’s traditional boundaries to founders and builders of AI-native products, growth infrastructure, or internal platforms. What matters most is a deep understanding of marketing, strong technical instincts, and the ambition to imagine a fundamentally better way of working. In this role, you will: Define the vision, strategy, and operating model for Marketing Operations & Technology, including how AI should reshape the function. Build and lead a team spanning market

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 a Operations Program Manager (OPM) to serve as the single-threaded operational leader for new hardware introductions (NPI) and production ramps across OpenAI’s AI infrastructure systems. This role combines hands-on execution with strategic ownership. You will be responsible for defining the operating model, aligning cross-functional stakeholders, setting the critical path, making informed tradeoffs, escalating decisively, and ensuring hardware programs deliver on schedule, quality, cost, and scalability. Success in this role requires comfort operating in ambiguity, influencing without authority, and driving alignment across internal teams and external partners—while keeping eyes firmly on long-term system scalability and repeatability. In this role, you will: Strategic & Leadership Ownership Act as the single-threaded owner for operational readiness across NPI and ramp, accountable for outcomes from early bring-up through sustained production Translate OpenAI’s infrastructure strategy and engineering objectives into clear operating plans, execution priorities, and decision frameworks Drive alignment across Engineering, Operations, Strategic Sourcing, Finance, Capacity Planning, and Executive stakeholders by framing tradeoffs, risks, and recommendations Proactively identify inflection points where decisions or investments are required to protect long-term scale, reliability, or cost targets Influence operational strategy with manufacturing par

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. Role summary We are seeking a Networking Operating System Firmware Engineer to help bootstrap and scale the switching layer of our AI supercomputers. In this role, you will build and maintain custom NOS images from scratch, using open source components from SONiC, SAI, FRR, and related networking stacks while working across the Linux kernel, switch ASIC SAI/SDKs, platform drivers, control-plane services, and orchestration layers. This is a software engineering role that requires a deep understanding of networking, NOS internals, switch hardware, and production systems. You will design, implement, test, and debug production NOS software across platform drivers, routing and control-plane state, ASIC programming, observability, and fleet integration. The engineer in this role should be able to work through ambiguous, open-ended technical problems and drive feature development across software, hardware, and vendor boundaries. 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 Design, develop, and maintain custom NOS images for large-scale AI fabrics, using open source components from SONiC, FRR, and related networking stacks. Integrate, build and configure Linux kernel components, device drivers, switch ASIC SDKs, and SAI layers. Bring up new switch platforms, including thermal and fan control, power monitoring, transceiver management, watchdogs, OSFP CMIS, L

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 looking for an embedded engineer to help build firmware and associated modeling software for OpenAI’s in house AI accelerator. This role involves designing and developing drivers and functional models for a large array of HW components, writing high throughput and low latency firmware code, investigating bring-up and production issues. Responsibilities Design and implement drivers for hardware peripherals, including those related to AI chips. Design and implement functional software models to simulate SoC uncore logic and enable FW testing against the model Design and implement low-latency and high throughput embedded SW to manage HW resources. Work with adjacent software and hardware teams to implement requirements, debug issues and shape future generations of the hardware. Collaborate with vendors to integrate their technologies within our systems. Bring up and debug firmware/driver on new platforms. Come up with processes and debug issues raised in the field. Set up monitoring, integration testing and diagnostics tools. Qualifications 5+ years of experience working in embedded SW space. Ability to thrive in ambiguity and learn new technologies. Strong programming skills in C/C++ and/or Rust. Experience developing high throughput, low latency and multi-threaded code. Experience working with real time operating systems (RTOS). Experience developing hardware drivers and working with hardware Experience with HW/SW co-design Knowledge of common embedded pr

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We’re looking for signal integrity (SI) system design engineers who have a deep expertise in the SI area, and hold strong system level design knowledge 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 system signal integrity (SI) design for AI supercomputer product in the data center application. Collaborate with chip, package, boards, rack and system engineers, design partners to drive system SI design and develop innovative interconnect and high-speed technologies Identify and evaluate new technologies and methodologies to improve signal and power integrity in product design, and contribute to the development of new products and technology by providing expertise in signal integrity Perform simulation and modeling to identify and troubleshoot signal integrity issues Lead system interconnect design, bring up and qualification As the scope of the role and team grows, understand and influence roadmaps for hardware partners for our datacenter networks, racks, and buildings. You might thrive in this role if you: Have at least 10 years of industry experience, including experience design hardware system and SerDes testing for data center applications Have a strong bias toward action, and won’t take no for an answer. Have experience and good knowledge of system design experience in the SI areas, from chip, SerDes, board, rack level Have ex

About the Team The OpenAI 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 peoples’ lives. About the Role OpenAI Robotics depends on high-quality real-world robot data from a large, live operational environment. That environment has many deployed workcells, changing configurations, and little tolerance for downtime. We are seeking a Field Engineer to help keep that environment running well. You will own the day-to-day technical health of robotic workcells used in ongoing data acquisition operations, diagnose and resolve failures across hardware and software, and build the practical tools, documentation, and support workflows that make operators and technicians more effective. The work is close to the floor, close to the failure modes, and close to the research impact. This role sits at the intersection of software, robotics hardware, and live operations. The best people in it are practical, technically sharp, calm under pressure, and motivated by making real systems work reliably at scale. This role will be based in San Francisco, CA 5 days per week and offer relocation assistance to new employees. In this role, you will: Serve as an engineering owner for keeping a fleet of robotic workcells online in daily operation. Diagnose, fix, mitigate, or escalate issues spanning mechanics, electronics, controls, software interfaces, logs, and configuration. Partner closely with technicians, operators, and engineering teams to improve scalable fleet support processes. Build or spec lightweight hardware and software tools that improve monitoring, diagnostics, recovery, and handoffs. Create documentation, SOPs, and diagnostic playbooks that turn en

About The Team Our mission is to bring OpenAI products to life for every customer. Demo Experience equips customer-facing teams with the experiences, systems, and confidence to make frontier capabilities tangible, relevant, and trustworthy. OpenAI’s products and customer needs are evolving rapidly. Demo Experience closes the gap between a frontier capability and a credible customer experience—making new capabilities understandable, demonstrable, and reusable quickly at scale. Working across Product, Engineering, Marketing, Operations, and GTM, we turn recurring customer needs into reusable capabilities and raise the standard for every customer conversation. About The Role Demo Experience Engineers work at the intersection of product engineering, technical storytelling, and GTM execution. You will own ambiguous, high-leverage problems end to end—from building agentic prototypes to creating the infrastructure and self-service tools that make them reliable and reusable. Your work will help customer-facing teams move faster, reduce avoidable failures, and translate frontier product capabilities into clear customer value. You will also turn recurring patterns from customer-facing work into product feedback, launch-readiness improvements, and scalable systems. Success in this role means teams can demonstrate new capabilities sooner and with greater confidence. Recurring requests become reusable capabilities instead of one-off work. Demo experiences are accurate, reliable, and safe. Insights from customer-facing work improve product and readiness 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 Own end-to-end demo readiness for new and priority product capabilities, including environments, integrations, synthetic data, evaluations, reliability checks, and fallback paths. Build compelling prototypes, LLM agents, and reference flows that mak

About the Team The Codex Core Agent team builds the kernel of Codex. We own making the agent better, accelerating research, and making those improvements real in production for our users. That means working across the systems that make Codex actually function as an agent in the real world: the production performance envelope around tokens, latency, reliability, cost, and capacity; the core execution loop and interfaces that turn models into useful behavior; the shared infrastructure that enables other teams to build on Codex; and the feedback loops that turn real-world usage into better models and better agent behavior over time. About the Role We’re looking for engineers to build the infrastructure that powers Codex agents in production. This role focuses on the systems that let models safely execute code, interact with tools, complete long-running tasks, and operate reliably and efficiently at scale. You’ll design and operate the infrastructure behind sandboxed execution, orchestration, stateful workflows, app-server and SDK boundaries, and model rollouts. You’ll work at the intersection of distributed systems, developer tooling, and AI, building primitives that make Codex faster, safer, more reliable, and easier for the rest of the organization to build on. What You’ll Do Design and build execution environments for AI agents, including sandboxing, isolation, and reproducibility. Develop systems for agent orchestration across multi-step, tool-using workflows. Build infrastructure for running, testing, and debugging code generated by models. Create state and memory systems that allow agents to persist context across long-running tasks. Optimize tokens, latency, reliability, and cost across Codex’s production fleet. Support model rollouts, capacity planning, and the core tradeoffs between quality, speed, and economics to manage a fleet of frontier agents at scale. Build shared platform capabilities that unblock product teams, partner teams, and open source Codex. Yo