Engineering Manager Jobs

About the Team: The Database Systems team specializes in high-performance distributed databases. Our team built Rockset, the real-time search, analytics, and vector database that powers all vector search and retrieval augmented generation (RAG) at OpenAI. In addition to retrieval, as an online database, Rockset powers core functionality across all of OpenAI's product lines and many critical internal use cases. About the Role : We are looking for engineers passionate about distributed systems, close-to-the-metal performance optimization (our core engine is written in C++), and building scalable database infrastructure from the ground up. As an engineer on the Database Systems team, you'll contribute to the core database engine, driving improvements across ingestion, query execution, indexing, and storage. You'll partner with teams across OpenAI to unlock new product capabilities and help scale online database reliability and throughput as usage grows by orders of magnitude. In this role you will: Design, build, and operate high-performance distributed systems Identify and resolve performance bottlenecks to scale infrastructure to the next order of magnitude Define long-term technical direction and guide system evolution Collaborate with product, engineering, and research teams to deliver scalable and reliable infrastructure Dig deep into complex production issues across the stack Contribute to incident response, postmortems, and best practices for system reliability You might thrive in this role if you: Have significant experience building, scaling, and optimizing distributed systems at scale Are curious about database internals, storage engines, or low-latency query systems Enjoy debugging challenging performance issues in complex, high-throughput systems Have experience operating production clusters at scale (e.g., Kubernetes or other orchestration systems) Think rigorously about scalability, correctness, and reliability Thrive in fast-paced environments with high

About the Team The Cooperative AI team is scaling OpenAI with OpenAI. We are building a model powered knowledge system that evolves and learns as our products, systems and customers evolve. We leverage our state of the art models, technologies, and products (some external, some still in the lab) to assist or completely automate robust operations supporting both internal and external customers. We support OpenAI customers and internal partners globally, powering systems from customer support to integrity to product insights. We are a self-contained multi-disciplinary team, who enjoy a lightning fast feedback loop with customers at scale, some of whom sit just a few pods away. We iterate fast, and engineer for reliable long-term impact. We're constantly looking for the similarities and patterns in different types of work, and focus on building simple primitives, to apply world class knowledge to many domains. The work of this team exemplifies use of OpenAI technologies. We build systems so everyone can see the leverage that is possible with well designed AI-based implementations. We do this by working through internal use cases focused on Customers (specifically knowledge systems, automation systems, and automated agent systems) to prove impact, then we scale. About the Role We’re looking for a Backend Software Engineer to help architect and scale the infrastructure that powers our knowledge systems. This is a deeply technical and highly cross-functional role where you’ll build robust systems and backend services that serve as the foundation for how knowledge is created, accessed, and applied across OpenAI. In this role, you will: Design, build, and maintain backend services and APIs to support intelligent automation and knowledge systems Integrate and structure data across internal platforms, transforming it into formats optimized for use by downstream systems and AI workflows. Collaborate closely with product, research, and engineering teams to integrate OpenAI mode

About the Team: OpenAI, in close collaboration with our capital partners, is embarking on a journey to build the world’s most advanced AI infrastructure ecosystem. Our Stargate program develops and deploys massive, state-of-the-art data center campuses in partnership with industry leaders today—and through future OpenAI infrastructure projects tomorrow. We design for scale, speed, and reliability, and we need experienced technicians who can translate network blueprints into physical reality. About the Role: We are seeking a Senior Data Center Networking Technician who thrives in fast-moving build environments and is eager to roll up their sleeves during active datacenter deployments. Your first assignment will focus on the physical bring-up of network infrastructure at a large partner-operated campus, collaborating with partner teams and their delivery vendors to achieve agreed performance and reliability targets. As that campus reaches steady state, you will transition to lead network deployment for future OpenAI data center projects, defining standards and guiding implementation across multiple locations. Candidates must be able to sit onsite in Abilene, Texas 5 days per week Key Responsibilities Serve as OpenAI’s technical lead technician during the current campus build, partnering with internal engineers and external contractors on design reviews, installation plans, and acceptance criteria. Spend significant time on the data-center floor performing inspections, assisting with cable routing/termination when needed, conducting fiber testing (OTDR, power levels, continuity), and resolving installation challenges in real time. Troubleshoot and optimize cabling routes, patching, and equipment turn-up to ensure clean, reliable handoff to network operations. Contribute to design discussions and peer reviews for structured cabling and physical network layouts, providing practical field feedback to engineering teams. Develop repeatable engineering standards, as-built do

About the Team At OpenAI, we’re building safe and beneficial artificial general intelligence. We deploy our models through ChatGPT, our APIs, and other cutting-edge products. Behind the scenes, making these systems fast, reliable, and cost-efficient requires world-class infrastructure. The Caching Infrastructure team is responsible for building a caching layer that powers many critical use cases at OpenAI. We aim to provide a high-availability, multi-tenant cache platform that scales automatically with workload, minimizes tail latency, and supports a diverse range of use cases. We’re looking for an experienced engineer to help design and scale this critical infrastructure. The ideal candidate has deep experience in distributed caching systems (e.g., Redis, Memcached), networking fundamentals, and Kubernetes-based service orchestration. In This Role, You Will: Design, build, and operate OpenAI’s multi-tenant caching platform used across inference, identity, quota, and product experiences. Define the long-term vision and roadmap for caching as a core infra capability, balancing performance, durability, and cost. Collaborate with other infra teams (e.g., networking, observability, databases) and product teams to ensure our caching platform meets their needs. You Might Thrive In This Role If You: Have 5+ years of experience building and scaling distributed systems, with a strong focus on caching, load balancing, or storage systems. Have deep expertise with Redis, Memcached, or similar solutions, including clustering, durability configurations, client-side connection patterns, and performance tuning. Have production experience with Kubernetes, service meshes (e.g., Envoy), and autoscaling systems. Think rigorously about latency, reliability, throughput, and cost in designing platform capabilities. Thrive in a fast-paced environment and enjoy balancing pragmatic engineering with long-term technical excellence. About OpenAI OpenAI is an AI research and deployment company d

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 peoples’ lives. About the Role We're seeking talented Robotics Software Engineers to expand our robotics data collection and evaluation program. This highly technical role involves designing, implementing, and optimizing software solutions across diverse robotics hardware. You'll work closely and collaboratively with multidisciplinary teams; including software, hardware, research, and operations - to drive advancements in our robotic systems. This role is based in San Francisco, CA, and requires in-person 4 days a week. In this role, you will: Help develop and grow our data collection labs, owning the entire integration lifecycle, from identifying and sourcing new hardware to collaborating with mechanical and electrical engineers on setup, software integration, and operational deployment. Develop innovative robot control interfaces suited to a variety of morphologies, environments, and tasks. Collaborate closely with research and engineering teams to develop automation tools and machinery that facilitate the evaluation of advanced robotic policies. Lead the design and implementation of data collection, visualization, and quality control processes. You might thrive in this role if you: Have 5+ years of professional software engineering experience developing and shipping production-quality systems in robotics or hardware-integrated environments. Have extensive experience integrating and deploying industrial automation systems, off-the-shelf robotics platforms, or custom hardware into production environments. Bring hands-on experience delivering production-quality software

About OpenAI OpenAI is dedicated to ensuring that artificial general intelligence (AGI) benefits all of humanity. Our mission requires building not only world-class AI models, but also the infrastructure that enables those models to be deployed reliably, efficiently, and at global scale. As demand for AI continues to grow, we are expanding the ways OpenAI can bring high-performance inference capacity online across a diverse hardware ecosystem. About the Team The GPT Infrastructure team builds software that turns advanced inference and optimization research into production products. One focus is enabling strategic infrastructure partners and accelerator vendors to qualify and onboard new compute without a bespoke porting and optimization effort for every hardware platform. We build the control planes, APIs, secure partner-side execution environments, evaluation systems, artifact pipelines, and operational tooling that make these workflows repeatable and trustworthy. The work sits at the intersection of distributed systems, AI inference, compilers and runtimes, performance engineering, security, and external partnerships. About the Role We are seeking an experienced systems generalist who can work comfortably across the stack to help build an automated inference optimization platform. Given a workload, target hardware profile, compiler and runtime context, and a trusted verifier, the system runs durable optimization campaigns that generate, compile, execute, grade, and improve candidate kernels, runtime configurations, and serving-stack changes. You will design both the OpenAI-hosted control plane and the partner-side software that evaluates candidates on real accelerator hardware. The product must keep long-running workflows reliable, make performance results reproducible, and maintain clear trust boundaries around sensitive model and hardware information. This is a deeply cross-stack role, combining strong software engineering fundamentals with systems thinking and

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 We are building general-purpose robotics. In the short term, we are focused on robots to support skilled workers to build our future infrastructure. In the long term, we imagine everyone having a personal robot doing anything they need. Progress is rapid, and based on a foundation of co-design between robotics hardware and ML research. About the Role As a Firmware Engineer, you will define and drive the architecture of embedded systems for next-generation hardware products. You will own foundational firmware decisions across real-time execution, device bring-up, hardware interfaces, fault handling, safety mechanisms, and production readiness. We’re looking for someone with deep experience building safety-critical or high-consequence systems, where failures can have meaningful consequences. You should be comfortable reasoning about risk, designing for diagnosability and graceful degradation, and creating engineering practices that raise the reliability bar for the entire team. You should also be unusually good at moving fast. Sometimes the right answer is a carefully reviewed architecture that will endure for years; sometimes it is getting a rough-but-useful prototype working by the end of the afternoon so the team can learn something concrete tomorrow. We value engineers who know the difference, make that call well, and can operate credibly in both modes. You will be both a technical leader and a hands-on builder: setting direction, reviewing critical designs, unblocking the hardest problems, and writing production firmware when it matters most. Our embedded stack uses a lot of Rust. Extensive experience in the language is a big help! 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: Rapidly bring up new hardware and set execution pace for the team. Lead firmware architecture for embedded systems spanning boot, RTOS/runtime behav

About the Team The Codex Research team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of the Codex Research team, you will improve the capabilities, reliability, and product fit of OpenAI's agentic models. You might own a research direction, build the infrastructure that makes large training runs faster and more trustworthy, create evals that reveal where models fail, or drive a capability from an idea through experimentation, integration, and launch. This role is intentionally broad. The strongest candidates are not defined by one method or subfield; they are people who can take an ambiguous capability problem and make progress across research, engineering, data, evals, and product. You should be excited to work on models that act in the world: writing and debugging code, using tools, calling functions, operating computers, collaborating with other agents, and completing valuable work on behalf of users. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measu

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 peoples' lives. About the Role You will work at the cutting edge of OpenAI's robotics hardware, partnering with hardware and software teams to develop, build, test, and iterate on robotic systems. Working closely with engineers, you will build prototypes, execute experiments, fabricate fixtures, troubleshoot hardware, and help drive rapid iteration on new robotic technologies. Your practical problem-solving and technical judgment will help move projects from concept to reality. We are looking for versatile, hands-on generalists who enjoy solving problems across mechanical, electrical, fabrication, and experimental domains. The ideal candidate will have strong experience in high-velocity and early-stage hardware development environments, provide thoughtful feedback to engineering teams, and help improve both hardware and development processes. This role will help accelerate robotics development by enabling fast, high-quality iteration on new hardware concepts and systems. This role is based in San Francisco, CA, and is in-person 5 days a week. In this role, you will: Partner closely with engineers, researchers, and other members of the robotics team to support prototype development, experimentation, and hardware iteration. Build, modify, troubleshoot, and repair robotic systems and electromechanical assemblies spanning structural, electrical, sensing, and actuation subsystems. Design and fabricate fixtures, adapters, test equipment, and other prototype hardware that accelerate development efforts. Execute low-volume builds, engineering changes, and rework activities acro

About the team OpenAI’s mission is to build safe artificial general intelligence (AGI) which benefits all of humanity. This long-term undertaking brings the world’s best scientists, engineers, and business professionals into one lab together to accomplish this. In pursuit of this mission, our Go To Market (GTM) team is responsible for helping customers learn how to leverage and deploy our highly capable AI products across their business. The team is made of Sales, Solutions, Support, Marketing, and Partnership professionals that work together to create valuable solutions that will help bring AI to as many users as possible. About the role Our ChatGPT Enterprise Sales team has a unique mission to help customers understand the deep impact that highly capable AI models can bring to their business and users. This role is a mixture of technical understanding, vision, partnership, and value-driven strategy. Our EDU Account Director will specialize in working with education institutions and companies as they adopt OpenAI’s products. For example, this individual will focus on helping support universities K-12 institutions as they evaluate and adopt ChatGPT Enterprise for their administrators, faculty and students. You’ll be a key driver of opportunities through the entire sales cycle, from pipeline generation to closure. You’ll represent OpenAI as a thought leader in AI, and partner with researchers, engineers, and solution strategists to help customers evolve their AI journeys. ChatGPT Enterprise (launched Aug’23) is being rapidly adopted by companies around the world, and we’re looking for tenured Account Directors to join our team and continue to bring both new customers onto the product, and expand existing ones. This role is based in Sydney. We use a hybrid work model of 3 days in the office per week. In this role, you'll: Lead our enterprise prospects’ journeys from consideration to purchase. Partner with Account Associates, Solutions Engineering and Customer Success

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 OpenAI’s Legal team plays a crucial role in advancing our mission by tackling innovative and fundamental legal issues in AI. The team includes professionals from diverse legal fields – technology, AI, infrastructure, privacy, IP, corporate, employment, tax, regulatory, and litigation – who collaborate closely with colleagues across the company. If you are passionate about being a technology lawyer working on cutting-edge challenges, you’ll thrive here. About the Role We are seeking an experienced commercial attorney to join our commercial legal team. Based in the US, you will help lead commercial legal support for OpenAI’s rapidly growing business, working with teams such as GTM, Partnerships, Procurement, Finance, Product, Infrastructure, and Engineering. This is a great opportunity to join OpenAI’s commercial legal team, negotiating high-impact agreements and helping to build scalable frameworks for responsible growth. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week. In this role, you will: Serve as the legal partner for OpenAI’s business transactions, partnerships, and operations. Provide practical, business-oriented legal advice to teams including Sales, Partnerships, Finance, Procurement, and Operations. Identify and address commercial, product, regulatory, privacy, and other legal issues arising from commercial transactions. Develop strategies and processes for handling legal issues in creative and scalable ways that support growth. Monitor and advise on regulatory and compliance matters affecting AI and technology. Collaborate with colleagues across OpenAI’s global legal team to ensure alignment across jurisdictions. You might thrive in this role if you: Have 7+ years of experience across in-house and technology-focused law firm roles. Bring a strong background in drafting and negotiating complex commercial contracts. Are comfortable operating in an entrepreneurial environment, and are proact

About the Team The Synthetic RL team develops reinforcement learning methods that leverage synthetic data, environments, and feedback to train and evaluate frontier AI models. The team explores approaches such as self-play, simulators, and other synthetic evaluations to push model capability, generalization, and alignment beyond what is possible with the current prevailing methodology. About the Role As a Research Scientist on the Synthetic RL team, you will develop novel reinforcement learning techniques that use synthetic environments and feedback to improve large-scale models. You’ll work closely with other researchers to design experiments, analyze learning dynamics, and translate research insights into training approaches used in production systems. We’re looking for researchers who enjoy working on open-ended problems, value fast iteration, and want their work to directly shape how frontier models are trained. 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: Research and develop reinforcement learning algorithms Design and run experiments to study training dynamics and model behavior at scale Collaborate with engineers and researchers to integrate successful approaches into model training pipelines You might thrive in this role if you: Have a strong background in reinforcement learning, machine learning research, or related fields Have strong engineering and statistical analysis skills Enjoy exploring new problem spaces where data, objectives, and evaluation are imperfect or evolving Are motivated by seeing research ideas influence real-world AI systems 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 ex

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