Quality Assurance Manager in United States

About the Team OpenAI is building AI systems that can help professionals perform complex, high-value work with greater speed, rigor, and creativity. Investment banking is one of the most demanding environments for knowledge work: bankers must synthesize fragmented information, exercise judgment under pressure, and produce precise, defensible models, analyses, and client materials. Our team works across Research, Product, Engineering, and Go-to-Market to make OpenAI's models genuinely useful for these workflows. We translate real professional work into product requirements, evaluations, training signals, and repeatable customer solutions. We care not only whether a model can generate an answer, but whether it can deliver accurate, defensible work that experienced bankers can trust and use. 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. About the Role We are looking for a Subject Matter Expert in Investment Banking to help define what excellent AI-assisted banking work looks like and turn that standard into better models and products. You will bring deep, current knowledge of how investment banking work is actually performed, including company and industry research, financial analysis and modeling, valuation, diligence, transaction execution, and the creation and review of client materials. You will use that expertise to design realistic tasks and evaluations, create and assess high-quality reference work, diagnose model failures, and help our technical teams improve model behavior and product experiences. This is a hands-on individual-contributor role for someone who enjoys both doing the work and explaining what makes it good. You should be comfortable moving between an Excel model, a presentation, a source document, an evaluation rubric, a product prototype, and a conversation with researchers or customers. You will help us distinguish outputs that merely look pl

About the Team The Applied AI team safely brings OpenAI's technology to the world. We released ChatGPT, Plugins, DALL·E, and the APIs for GPT-4, GPT-3, embeddings, and fine-tuning. We also operate inference infrastructure at scale. There's a lot more on the immediate horizon. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. We serve end-users directly through ChatGPT, and serve developers through our APIs, which power product features that were never before possible. About the Role The Engineering Acceleration team designs, builds and maintains the foundational systems that engineers use to build ChatGPT and the API. This is a fast-growing team and you will get a chance to own and define the strategy, vision, and plan for how to increase developer productivity. In this role, you will: Drive the design, development, and implementation of tools, systems, and processes that accelerate engineering velocity, reduce manual effort, and increase the quality of output. Use our latest AI tools to re-think how we can be the most productive team in the industry. Work closely with various teams within OpenAI to understand their workflows, challenges, and needs, and ensure the tools and systems built by the Engineering Acceleration team address these requirements. Bring new features and research capabilities to the world by partnering with product engineers to lay the necessary technical foundations. Guide and advise product engineering teams on best practices for ensuring observable, scalable systems. Like all other teams, we are responsible for the reliability of the systems we build. This includes an on-call rotation to respond to critical incidents as needed. You might thrive in this role if you: Have 5+ years of experience in engineering, including 3+ years of experience in infrastructure building tooling for developers. Have experi

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 a highly experienced RTL engineer to own critical on- and off-chip interconnect components for our custom AI accelerator platform. You will drive the microarchitecture and RTL implementation of scalable on-chip communication fabrics connecting high-bandwidth compute, memory, and I/O subsystems as well as purpose-built off-chip interfaces and protocols needed to enable custom computing at scale. This is a senior, hands-on engineering role with broad technical ownership. You will drive design from requirements through the full silicon lifecycle, from architecture definition and performance analysis through RTL implementation, verification closure, physical design convergence, bring-up, and production readiness. You will plan and oversee the work of junior engineers and help drive and develop productive engineering relationships with external partners and help manage partner execution. 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 the microarchitecture, RTL design, and delivery of major SoC interconnect components, including network-on-chip fabrics, switches, routers, bridges, protocol adapters, arbiters, and traffic-management logic as well as off-chip protocol bridges and interfaces. Drive third party engagements to develop novel networking and interface protocols and silicon IP while ensuring high quality and de

About Team Our Robotics team is focused on unlocking general-purpose robotics and advancing toward AGI-level intelligence in dynamic, real-world environments. Working across the full model and systems stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the physical constraints of real-world systems to improve people’s lives. About Role We are looking for an Operations Program Manager - Robotics Data Acquisition to own the day-to-day operating rhythm in our data collection facilities. You will work closely with operators, technicians, program managers, and engineers to keep rigs ready, campaigns moving, issues resolved, and performance improving. This is a hands-on operations role that requires you to be comfortable spending time on the floor, working through ambiguity, and using data to make the operation more reliable and efficient. This role is based in San Francisco, CA and requires in-person presence 5 days a week. In this role you will: Coordinate daily operations readiness across workstations, operators, materials. Track core operating metrics including utilization, cycle time, throughput, downtime, operator productivity, and data quality. Identify bottlenecks through workflow analysis, time studies, and capacity modeling, then drive practical fixes. Execute the rollout of new hardware, sensors, tools, and process changes with Engineering, Operations, Facilities, Supply Chain, and Safety. Identify equipment readiness issues and coordinate with technical support to keep workstations, and test equipment calibrated, configured, maintained, and ready for rollouts and evaluations. Lead root cause analysis for recurring operational issues and follow through on corrective actions. Provide operation input to create and maintain SOPs, work instructions, training materials, and process controls. Identify and flag resource constraints and manage issue escala

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 create learning experiences, programs, and resources that help customers move from initial understanding to sustained use and measurable impact. As our products, audiences, and programs grow, we need an operating foundation that keeps the content portfolio trusted, clarifies complex work, and helps the team deliver at a consistently high standard. This role offers the opportunity to build the operational foundation behind education programs that shape how enterprises adopt frontier AI. About the Role We are looking for a strategic operator to own the operating system behind Customer Education. You will work at the center of content, systems, and team execution: owning the health of our education content portfolio, running the team’s operating rhythm, and translating evolving business needs into scalable workflows and system requirements. The right person will raise the quality of execution across Customer Education. You will bring order, judgment, and follow-through to a fast-moving environment, making the function easier to run, easier to trust, and easier to scale. In this role, you will: Own the health and integrity of the Customer Education content portfolio, including lifecycle, governance, discoverability, reuse, and meaningful gaps. Ensure customer-facing teams can confidently find and use the right education resources at the right time. Run the team’s operating rhythm across priorities, ownership, timelines, dependencies, decisions, launch readiness, and follow-through. Turn ambiguous cross-functional initiatives into clear plans, workflows, responsibilities, and decision points. Design scalable processes and handoffs for how education programs are created, launched, maintai

About the Team The Coding team is reimagining how software is built in the AI era. We build tools and workflows that help software engineers work faster, tackle more ambitious projects, and spend less time on repetitive tasks. AI has already transformed how code is written, but software engineering extends far beyond coding. Our mission is to apply AI across the entire software development lifecycle (SDLC) — from design and implementation to code review, testing, debugging, issue remediation, maintenance, documentation, and user support. The team is also responsible for developer-facing Codex experiences including the Codex IDE Extension and the terminal interface, which are used daily by developers ranging from individual open-source contributors to some of the world’s largest engineering organizations. The team also works closely with the open-source software community, building tools that help maintainers and contributors manage increasingly complex projects. We believe AI can make open-source development more sustainable by reducing the operational burden of reviewing contributions, triaging issues, maintaining quality, and supporting growing communities. By building the future of software development, we're helping advance OpenAI's mission of ensuring that the benefits of AI reach people around the world. About the Role We’re hiring a Full Stack Software Engineer to help invent the next generation of AI-powered software development workflows. “Full stack” in this role means much more than traditional frontend and backend development. You'll own complete product experiences, spanning user interfaces, workflow orchestration, agent and prompt design, backend systems, and cloud infrastructure. This is a highly product-oriented role. You'll work directly on the workflows developers use every day, identifying bottlenecks and rethinking how software gets built in a world where AI agents are active participants in the development process. The features you ship will inf

About the Team The Cybersecurity Products team builds products at the frontier of AI and cybersecurity. Our work includes Codex Security and related cyber products that turn advances in model capability into dependable tools for defenders. We help teams find, validate, and remediate vulnerabilities, continuously improve the security of software, and test AI-powered applications before they reach production. About the Role As a Full Stack Software Engineer, you will build the product experiences and systems that make AI-powered security useful in real engineering environments. You will work across web surfaces, APIs, orchestration, data models, and integrations to help security and engineering teams move from a codebase or application to evidence-backed findings, prioritized remediation, and revalidation. You will collaborate closely with product engineers, security researchers, and customer-facing teams. The work spans fast-moving product development and hard systems problems: long-running workflows, large repositories, sensitive data, reliability, observability, and a high bar for earning user trust. 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: Build end-to-end workflows for vulnerability discovery, security scanning, red teaming, findings review, remediation, and reruns. Design and operate backend services for long-running security work, including APIs, asynchronous orchestration, durable state, and integrations with developer workflows. Make complex security results actionable through clear product surfaces, strong evidence, thoughtful prioritization, and reliable reporting. Partner with security researchers, product teams, and users to evaluate quality, reduce noise, improve coverage, and ship safely. You might thrive in this role if you: Have experience shipping production full-stack products across modern web frontends and backend s

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 Enterprise Platform team builds the systems that help our GTM teams bring OpenAI products to customers at scale. This role sits close to our emerging ads business, partnering with Ads Sales, Operations, Product, Finance, Legal, and Engineering to create reliable workflows for advertiser lifecycle, campaign readiness, approvals, and revenue operations. About the role Our GTM team helps customers understand the transformational potential of OpenAI’s models, and our internal systems should make that work faster, cleaner, and more intelligent. We’re looking for a Salesforce Ads Systems Engineer to design and build the Salesforce foundation for our ads business. You’ll partner with Ads Sales, Ads Operations, Product, Finance, Legal, and data teams to turn complex advertiser and campaign workflows into scalable, auditable systems. This is an execution-heavy, builder role. The primary charter of this role is ads GTM systems: advertiser account and opportunity workflows, campaign/order readiness, approvals, integrations, and automation that keep ads motions moving cleanly from pipeline through launch, billing, measurement, and reporting. In this role, you'll: Build Salesforce solutions for ads GTM : Develop user experiences, objects, automations, and guardrails that help Ads Sales and Operations manage advertisers, opportunities, insertion orders, campaign readiness, approvals, and launch handoffs with high data quality. Engineer integrations across the ads stack : Connect Salesforce with ads platforms, product catalogs, pricing/rate-card systems, data warehouses, billing tools, measurement workflows, CLM, and e-signature systems so advertiser and campaign data stays accurate and audit

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 As a Supply Chain Program Manager, you will own material readiness and supply chain execution for critical hardware programs spanning custom silicon, systems, memory, storage, networking, and rack infrastructure. You will work cross-functionally with Engineering, Strategic Sourcing, Manufacturing Operations, Finance, Planning, Quality, and external suppliers to develop and execute scalable supply strategies that support aggressive product development and deployment timelines. This role requires deep understanding of hardware supply chains, material planning, NPI execution, supplier management, and operational scaling in constrained and rapidly evolving environments. In this role you will: Material Readiness & Supply Planning - Own end-to-end material readiness across NPI and production phases, including building the necessary framework and processes for enablement. Drive supply planning and execution for long lead-time and constrained commodities including ASICs, HBM, DDR, SSDs, networking, optics, power, thermal, and mechanicals. Build and manage material readiness plans aligned to proto/pre-EVT, EVT, DVT, PVT, and mass production schedules. Monitor supply health, lead times, inventory positions, allocation risk, and capacity constraints. Drive shortage management, allocation mitigation, and recovery planning. Coordinate supply commits, forecast alignment, and supply continuity planning with suppliers and manufacturing partners. Cross-Functional Program Ma

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the role Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own technical delivery across multiple deployments from first prototype to stable production Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Scope work, sequence delivery, and remove blockers early Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks that others can use Share field feedback that helps Research and Product understand where the models succeed and where they can improve Keep teams moving through clarity and follow-through You might thrive in this role if you Bring 5+ years of engineering or technical deployment experience that includes customer-facing work Have scoped and delivered complex systems in fast-moving or ambiguous environments Write and review production-grade code across frontend and backend using Python, JavaScript,

About the Team Business Systems / Enterprise Platform Technology builds the internal systems, data foundations, workflow infrastructure, and enterprise platforms that help OpenAI operate at scale. The EPT AI Pod builds AI-native internal apps, MCP connectors, multi-agent workflows, and reusable platform capabilities across Finance, People, and GTM. About the Role As an Enterprise Applied AI Engineer, you will build internal apps for enterprise operations and the shared platform components those apps run on. This includes MCP connectors, multi-agent orchestration, data architecture, evals, monitoring, auditability, and governance. We’re looking for a hands-on engineer who is strong in Python, system design, enterprise integrations, data architecture, and applied AI systems. You should be excited to turn ambiguous business workflows into reliable internal products and shared infrastructure. In this role, you will: • Build internal apps for enterprise operations across Finance, People, and GTM • Build MCP connectors and enterprise integrations with strong auth, permissions, idempotency, retries, and rate-limit handling • Design end-to-end multi-agent workflows with tool routing, human approvals, audit trails, and safe action boundaries • Design data architecture for operational AI systems, including ingestion, schemas, quality checks, lineage, and governance • Build evals, monitoring, metrics, and regression tests for agentic workflows • Create reusable infrastructure, patterns, and components that other enterprise teams can build on • Partner with system owners and business owners to turn messy enterprise workflows into reliable internal products You might thrive in this role if you: • Have strong Python engineering skills for backend services, MCP connectors, agent/tool workflows, eval harnesses, and data ingestion jobs • Have strong system design skills across shared infrastructure, app architecture, reliability, and scaling • Have experience building internal apps,

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the role As a foundational FDE manager, you’ll lead FDE through high-stakes, ambiguous customer deployments and own technical and business value outcomes end to end. You’ll grow a team that can operate under pressure and help OpenAI learn from the field. You’ll partner closely with Product, Research, Sales, and GTM to ensure fieldwork informs roadmap priorities, drives new exploration, and supports safe deployment at scale. Your decisions will influence how OpenAI is trusted by the customers closest to our deployment work. Your success will be measured by how consistently your team ships, how clearly you deliver signal to Research and Product, and how durable your team and delivery model prove to be. This role is based in New York City We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. This role also will require travel up to 25%. In this role you will Lead and grow a team of FDE delivering production systems with frontier models Own end-to-end delivery outcomes through clarity, speed, tight coordination, and technical quality Codify what works into tools, playbooks, and roadmap inputs that create leverage for both OpenAI and our wider developer community Notice early indicators and raise them with urgency, whether in product behavior, customer environments, or delivery practices Use judgement to distinguish what requires action and what does not Set a high bar for FDE performance and support each person’s growth through direct, actionable feedback Define how we staff and support field teams that can scale without added complexity You might thrive in this role if you Bring 8+ years of engineering or technical delivery experience, including 2+ years managing high-performing FDE or custo

About the Team The Monetization team is a new cross-functional group working across engineering, product, research, and design to build the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to develop user-first, privacy-preserving monetization products, including next-generation ads experiences, that strengthen user trust, unlock economic opportunity, and support OpenAI’s long-term innovation. Monetization plays a critical role in enabling OpenAI to continue pushing the boundaries of AI capabilities while ensuring the benefits of AGI are broadly shared. We believe monetization must be aligned with user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem of developers, advertisers, and businesses. This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, and Research to bring new ad experiences into real-world systems across OpenAI surfaces at global scale, including thoughtfully integrating them into the core ChatGPT experience. About the Role We’re looking for an experienced Software Engineer to help build the creative rendering and presentation layer of OpenAI’s ads ecosystem. This is a foundational role responsible for defining how ads are structured, rendered, and delivered across different surfaces, platforms, and media types. You’ll work across the full technical stack to build infrastructure and tooling for new ad formats, including text, image, video, native, conversational, and interactive experiences. You will help ensure these formats render reliably, perform efficiently, and feel natural within the core ChatGPT experience. You’ll collaborate deeply with Product, Design, and Research to create ads experiences that are useful, high-quality, privacy-preserving, and aligned with OpenAI’s standards for safety and user trust. In this role, you will: Design, build, and

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 As a Senior Software Engineer, ML Systems & Training Infrastructure, you will be a deeply hands-on engineering force multiplier for the robotics team. You will help keep the training framework and surrounding infrastructure healthy, review and improve code quickly, debug failures across ML systems and infrastructure, and unblock researchers and engineers when the path from idea to working training job gets rough. We’re looking for people who love writing, reading, reviewing, and fixing code; who can get productive quickly in unfamiliar systems; and who bring strong practical judgment without a lot of ego or process overhead. This role will be based in San Francisco, CA and be expected in office 5 days per week and offer relocation assistance to new employees. In this role, you will: Review, improve, and clean up code across training frameworks and adjacent infrastructure. Identify risky or low-quality changes before they land, and raise the code quality bar without slowing the team down. Debug issues across ML training systems, GPUs, clusters, networking, and related infrastructure. Help researchers and engineers unblock broken training jobs, flaky workflows, and brittle internal tooling. Improve the reliability, maintainability, and usability of the robotics team’s training framework. Move quickly on practical engineering problems that directly affect team velocity. You might thrive in this role if you: Have strong software engineering fundamentals and excellent code review judgment. Have experience with ML systems, training fr

About the Team OpenAI's Research Data Team exists to accelerate the evaluation, safety and capabilities of our models and products. Made up of technical operators and software engineers, we design the methods in which we acquire and create data. About the Role As a Research Program Manager (RPM), Data Acquisition, you will partner with research, engineering, and operations to design and implement pragmatic solutions for acquiring data. You will be a key interface between our research roadmap and external data offerings. This role is based in our San Francisco HQ and will be part of a team of RPMs pushing the frontier of data acquisition. In this role, you will: Partner deeply with research: Work with researchers to scope data needs, define success criteria, and translate priorities into clear execution plans. Shape the data acquisition pipeline: Identify, evaluate, and advance high impact data opportunities - balancing research value, feasibility, quality, and responsible execution. Unblock yourself: Move work forward even when the path is unclear — using technical judgement, creative problem solving, and scrappy execution to make progress while longer-term solutions are still forming. Build lightweight systems and visibility: Use SQL, Python, dashboards, and simple tooling to track performance, quality, and blockers. Drive technical roadmaps: Collaborate with engineers to enhance data platforms, resolve blockers, and ensure security best practices such as access management. Scale your impact: Equip vendors and internal teams with the context, standards, and operating rhythms needed to focus on the most important problems. You’ll thrive in this role if you: Are proficient in SQL and Python for analysing datasets, querying databases, building dashboards, and generating actionable insights. Are comfortable using APIs, automation, and AI tools such as Codex to accelerate workflows, remove manual overhead, and upskill quickly in unfamiliar technical areas.Experience sou