Developpeur Logiciels in United States

About the Team The Product Marketing team shapes how customers understand, adopt, and realize value from OpenAI’s technology. We work across Product, Research, Sales, Solutions, Partnerships, and Customer Success to bring customer insight into our product strategy and translate technical capabilities into clear, credible stories and solutions. About the Role AI becomes meaningful when it helps people do the work that matters to them. For a finance team, that might mean understanding complex information faster. For a healthcare provider, it might mean navigating clinical workflows more effectively. For a sales or marketing team, it might mean creating entirely new ways to reach and serve customers. We’re looking for a senior product marketing leader to shape how OpenAI serves the business functions and industries where our technology can make a meaningful difference. You’ll define how our models and products meet the needs of teams such as sales, marketing, and finance, as well as industries including financial services, healthcare, and retail. Working closely with Product, Research, Sales, Solutions, and Partnerships, you’ll identify important customer problems, influence product strategy, and build relationships with the ecosystem partners and data providers needed to bring complete solutions to market. You’ll also build and lead the product marketing team responsible for turning these opportunities into durable customer value. You might thrive in this role if you: Have 12+ years of experience in product marketing, industry marketing, solutions marketing, or enterprise go-to-market, ideally across enterprise software, cloud, data, developer, or AI platforms. Have built and led high-performing teams, mentored senior marketers, and know how to create clarity in fast-moving, ambiguous environments. Understand how different industries and business functions evaluate technology, adopt new tools, and define value. Have shaped positioning and go-to-market strategies for c

About the Team At OpenAI, our Trust, Safety & Risk Operations teams safeguard our products, users, and the company from abuse, fraud, scams, regulatory non-compliance, and other emerging risks. We operate at the intersection of operations, compliance, user trust, and safety working closely with Legal, Policy, Engineering, Product, Go-To-Market, and external partners to ensure our platforms are safe, compliant, and trusted by a diverse, global user base. The Global Safety Response Operations team within the org provides 24/7 coverage for user safety, risk, and regulatory escalations across OpenAI’s products, handling the highest-priority cases that require human judgment and rapid response. The team operates as the core escalations management and delivery arm of OpenAI’s safety operations, ensuring that our products remain safe and aligned with our policies while enabling timely, empathetic, and consistent user support. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. Please note: This role may involve exposure to sensitive content, including material that is sexual, violent, or otherwise disturbing. About the Role We’re looking for experienced Trust, Safety, and Risk Operations analysts who have subject matter expertise in one or more of the following areas: policy enforcement and content moderation, fraud and scam prevention, developer risk, or privacy and regulatory escalations. You’ll be on the front lines of safety escalation management, helping to triage and resolve urgent and sensitive cases. You’ll work across subject matter areas, systems, and processes to ensure operational excellence, develop process improvements and automations, and surface insights and trends. This is a 24/7 global operation that requires flexibility to work rotating shifts, including nights, weekends, and holidays, as part of an on-call coverage model. We use a hybrid work model of 3 days in the office per week and offer r

About the team The Agent Enablement AI Deployment Engineering (ADE) team works across engineering, product, design, partnerships, and strategic customers to grow an open ecosystem of agent-enabled sites and services. We help partners adopt the OpenAI tech stack related to identity, permissioning, agent-auth primitives so users can safely connect ChatGPT and Codex to the tools, services, and workflows they already use. Our team also works with external partners on defining the standards for agent access, marketplace offerings as well as other agent enablement initiatives to ensure users of ChatGPT and Codex go from intent to task completion seamlessly. About the role We are looking for an AI Deployment Engineer to help strategic partners design, build, validate, launch, and operate agent enablement integrations across web applications, connectors, APIs, CLIs, MCP servers, and developer tools. This is a hands-on, partner-facing product engineering role for someone who can contribute to the platform itself, lead sophisticated technical engagements, and turn ambiguous identity and agent-workflow requirements into secure, production-ready integrations. You will work across partner product and engineering teams and OpenAI’s product, engineering, design, partnerships, legal, policy, security, support, and go-to-market teams. You will identify high-value user journeys, choose the right integration path, prototype and review architectures, write code, run evaluations and dogfood, trace failures end to end, guide launch and rollout, and support post-launch iteration. The best person for this role moves fluidly between full-stack code, OAuth/OIDC and identity systems, product judgment, project leadership, and clear communication with engineers and executives. This role is a fit for a product-minded engineer who wants to stay close to users and partners while going deep on authentication, permissions, reliability, safety, and developer experience. The principle objective is to

About the Team The Systems Integration team is responsible for building the infrastructure, tooling, and validation systems that ensure our device software our device software is reliable, testable, and ready to ship. We design and maintain build systems, CI pipelines, automated test frameworks, and hardware-in-the-loop labs to enable rapid, safe product launches. Our work spans build systems, developer tools, systems integration, and cross-team collaboration to ensure developers can build reliably and ship with confidence. About the Role We are looking for an engineer to help evolve OpenAI’s Consumer Products build and continuous integration systems for a fast-growing engineering organization. This role sits at the intersection of developer productivity, build systems, distributed infrastructure, software quality, and on-device software. You will work on the systems that determine how quickly and confident engineers can move: Bazel-bazed builds, Buildkite pipelines, test coverage, remote caching and execution, CI observability, and tooling that helps engineers understand and fix failures quickly. Our mission is to enable OpenAI to ship software running on consumer devices rapidly with a high bar for correctness, reliability, and safety. The best version of this work is invisible when it succeeds: builds are fast, tests are trusted, CI failures are understandable, and engineers can focus on shipping products instead of fighting infrastructure. This role is based in San Francisco, CA. We use a hybrid work model of four days in the office per week and offer relocation assistance to new employees. In This Role, You Will Own and evolve Bazel and yocto-based build and test workflows in a polyrepo environment Design and maintain Starlark rules, macros, toolchains, and integrations that make builds hermetic, reproducible, and easy for teams to adopt Improve CI performance and reliability across Buildkite pipelines, including queue time, build time, cache hit rates, retry b

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. The Industrial Compute team is central to this mission, setting the core infra strategy and implementing this vision. From site selection to the buildout process, this team sits at the intersection of commercial, technical, strategy, and operations, interacting with teams and executives inside and outside of OpenAI. About the Role OpenAI is seeking a Real Estate Lead to own land acquisition strategy and site-control execution for our next-generation data center portfolio across the U.S. This role sits at the front end of infrastructure delivery, translating market intelligence, broker/developer relationships, and commercial judgment into credible shovel-ready positions that meet OpenAI’s power, land, permitting, and expansion requirements. The Real Estate Lead will not operate as a traditional transactional real estate function. The scope is to help shape where OpenAI can build, secure the right land positions early, structure defensible commercial terms, and coordinate the legal, technical, and development work required to move opportunities from sourced lead to controlled site and ultimately to readiness handoff. This is an individual contributor lead role and does not have direct reports initially. The role also owns market prioritization and portfolio-level acquisition strategy across target geographies, and is expected to run multiple negotiations in parallel while translating site-control work into executive-ready acquisition recommendations. Key Responsibilities Own market prioritization and portfolio acquisition strategy across target geographies, including scenario analysis for speed, scale, expansion potential, and risk-adjusted economics. Proactively source and evaluate land parcels at scale to support long-term data center growth across priority markets. Build and manage a national pipeline of

About the Team The Ecosystem AI Deployment Engineering (ADE) team supports strategic partners as they build high-quality technical integrations into ChatGPT and Codex. Our goal is to create products users depend on, drive adoption and retention, and build an ecosystem where partners win when OpenAI wins. About the Role We are looking for an AI Deployment Engineer to help strategic partners design, build, evaluate, submit, launch, and maintain high-utility plugins for ChatGPT and Codex. This is a hands-on, partner-facing product engineering role for someone who can contribute to the platform itself, lead sophisticated partner engagements, and translate ambiguous product needs into production-ready integrations. You will work across partner product and engineering teams and OpenAI's product, engineering, partnerships, legal, policy, design, and go-to-market teams. You will identify the right use cases, prototype and review implementations, run evaluations, debug issues across systems, guide partners through submission and review, and support launch and post-launch iteration. The best person for this role moves fluidly between code, product judgment, project leadership, and clear communication with engineers and executives. This role is a fit for a product minded engineer who wants to stay close to users and partners while still going deep on code, reliability, evaluations, and developer experience. The goal is to help partners ship plugins that are not merely technically functional, but genuinely useful in ChatGPT and Codex. This role is based in our San Francisco office. 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 technical partner journey for priority B2B plugins—from pitch and readiness assessment through architecture, build, evaluation, submission, launch, and ongoing maintenance. Identify strong plugin use cases, define crisp user journeys and expected behaviors, and

About the Team OpenAI’s Business Marketing team helps organizations understand, adopt, and create value with AI. Integrated Marketing connects our brand, products, customers, developer communities, go-to-market teams, and commercial priorities into coherent market moments. We are building an AI-native marketing team that moves quickly, uses intelligence to work differently, and measures success by whether business audiences become aware of OpenAI, consider our products, and ultimately choose us. About the Role We’re hiring an integrated marketer to shape how businesses understand, experience, and choose OpenAI. You’ll connect our brand, products, and customer stories into campaigns that demonstrate how AI is transforming organizations and establish OpenAI as a preferred partner for businesses adopting AI. You’ll build integrated campaigns for BDMs, and grow customer relationships through storytelling as a critical source of proof of enterprise transformation.. This role is part of the Integrated Marketing team within OpenAI’s Business Marketing organization. While your specialty is brand and customer, you’ll flex across business campaigns, product launches, and other priority market moments. In this role, you will: Lead integrated brand marketing strategies and campaigns that increase awareness, consideration, and preference among enterprise buyers and business decision makers. Synthesize audience research, cultural/competitive context, product truth, customer proof, and business priorities into positioning and creative briefs that can travel across paid, owned, earned, social, field, and sales channels. Connect brand, creative, customer marketing, communications, media, growth, demand generation, and field activation into one coherent business audience journey. Use AI to uncover insights, experiment with new storytelling formats, and accelerate high-quality execution. Be directly accountable for increasing unaided awareness, consideration, purchase preference, and

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 OpenAI is evaluating multiple infrastructure pathways, including powered land, colo/BTS, and NeoCloud opportunities. The Site Readiness & Development team provides the diligence layer needed to compare opportunities, identify risk, and support credible deployment decisions across those pathways. About the Role The NeoCloud & Colo Due Diligence Lead will evaluate third-party infrastructure opportunities where OpenAI is considering deployment through NeoCloud, colo, or BTS structures. This role will focus on facility and deployment readiness, including MEP readiness, rack strategy, developer capability, facility design, power deliverability, schedule credibility, and operating assumptions. Unlike the land diligence team, this role is centered on technical and operational readiness of third-party infrastructure rather than greenfield site master planning, civil development, and entitlement strategy. This is an individual contributor lead role and does not have direct reports initially. The role determines whether each opportunity is fit-for-use and fit-for-service against OpenAI facility, rack, power, network, reliability, and operational standards; identifies material deficiencies and tracks remediation with developers/operators; and evaluates commissioning, validation, AHJ/code, and deployment interfaces such as structured cabling, network readiness, and high-density rack support where relevant. Key Responsibilities Lead diligence on NeoCloud, colo, and BTS opportunities across technical and operational readiness dimensions. Assess each opportunity against OpenAI facility, rack, power, network, reliability, and operational standards to determine deployment fit. Validate MEP readiness, rack deployment strategy, facility design assumptions, power deliverability, and schedule credibility. Identify material deficiencies and work with developers/operators to define remediation plans, owners, timing, and residual risk. Review reliability, availabilit

About the Team OpenAI’s API Multicloud team is responsible for extending OpenAI’s API platform into strategic cloud environments, starting with AWS . The team’s mission is to distribute OpenAI’s API broadly and safely by enabling key API technologies in cloud-native environments, in close partnership with Amazon and internal teams across Codex, Research, Safety Systems, and Applied. The team is focused on bringing core developer and enterprise capabilities into cloud-native environments, including cloud-hosted Codex, model customization / post-training as a service, and new stateful runtime environments for agentic workloads. This work sits at the intersection of production ML systems, developer platforms, model behavior, and large-scale infrastructure. About the Role We’re looking for a backend engineer who can quickly understand OpenAI’s models, products, and systems, then adapt first-party deployments for other cloud platforms. You’ll build backend services, APIs, SDK integrations, authentication flows, and cloud service infrastructure that let developers use OpenAI capabilities in the cloud environments where they already build. This role involves working across teams, sometimes embedded with partner product groups, to ship products quickly and across multiple platforms at the same time. It’s a strong fit for engineers who have built developer tools, especially AI-powered tools, communicate clearly across technical boundaries, and can shape architectures that support different deployment models; experience building cloud services is a strong plus. In this role, you will: Build backend and infrastructure systems that extend OpenAI’s API platform into cloud-native environments, like AWS. Design and ship cloud-contained products that allow customers to use OpenAI capabilities while keeping workloads and data within cloud environments. Help stand up cloud-hosted Codex experiences powered by the OpenAI Responses API. Build the infrastructure and runtime abstractions

About the Team OpenAI’s API Platform organization builds the products and infrastructure that help first-party and third-party developers build with OpenAI models. We ship the API primitives, tools, SDKs, documentation, playgrounds, and platform experiences that make OpenAI’s capabilities reliable, understandable, and useful in production. The API Experience team is focused on the end-to-end developer experience for the OpenAI API. We own the surfaces developers touch every day: docs, SDKs, the Playground, examples, onboarding flows, and the systems that help developers go from first request to production deployment quickly and confidently. About the Role We’re looking for full stack and frontend engineers to help define and build the next generation of OpenAI’s developer experience. In this role, you’ll work across frontend product surfaces, backend systems, SDK and documentation pipelines, and API workflows that serve millions of developers and companies. You’ll partner closely with product, design, research, API engineering, and developer-facing teams to make complex AI capabilities simple to understand, easy to test, and safe to launch in real-world applications. This is a highly cross-functional role for someone who cares deeply about craft, developer empathy, reliability, and product velocity. In this role, you will: Build and scale developer-facing products including the OpenAI API Playground, documentation experiences, onboarding flows, examples, and API workflow tools. Own full stack projects end to end, from product definition and UX collaboration through backend implementation, launch, measurement, and iteration. Improve the systems that generate, maintain, and publish SDKs, API references, docs, guides, and developer examples. Partner with API, research, design, and infrastructure teams to bring new model capabilities and API primitives to developers in a clear, usable way. Use developer feedback, product analytics, and direct customer insight to identif

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 Cloud Agents team builds product infrastructure for long-running agents in the cloud: orchestration, sandboxing and isolation, secure environment connectivity, secrets and identity, observability, reliability, and cost controls. These agents securely connect to diverse developer and customer environments and use tools to accomplish goals. We partner closely with product, research, and infrastructure teams to turn agentic capabilities into dependable platforms for OpenAI products and developers building on OpenAI. About the Role We are looking for an experienced software engineer to help build and scale our cloud agent platform. You will design and operate systems for orchestrating agents at scale. You will work closely with product engineers on ChatGPT, API, and Codex to define the right abstractions and enable them to ship products quickly. Strong backend or infrastructure experience is important; experience with Python, Rust, distributed systems, cloud infrastructure, or product platforms is especially helpful. In this role, you will: Design and scale the orchestration, sandboxing and storage systems that run agentic workloads for Codex, ChatGPT, and the OpenAI API. Partner with product engineers to build a platform that enables them to ship quickly and turn feedback into robust abstractions. Improve reliability, security, performance, and cost efficiency for long-running agents. Deploy services that can operate across different environments and clouds. Your background might look something like: 9+ years of professional engineering experience, excluding internships, in relevant roles at technology and product-driven companies. Experience leading large-scale backend, platform, or infrastructure projects from ambiguous problem statements to production systems. Proficiency in one or more backend languages such as Python, Go, Rust, TypeScript, or similar, and the ability to move across service, platform, and product boundaries. Strong understanding

About the Team Training Runtime builds the distributed systems that power OpenAI's largest model training runs - most recently GPT-5.5! The Data Movement area owns the infrastructure that keeps training jobs supplied with the right data at the right time, and keeps model state moving safely and efficiently across large clusters. Our work spans machine learning systems, distributed storage, high-throughput data loading, reliability engineering, and developer experience. Success means researchers can move quickly while training runs remain fast, reproducible, debuggable, and resilient at scale. About the Role We are looking for a deeply hands-on Technical Lead Manager to own datasets throughout our training infrastructure. This person will set the direction for how training jobs read data: the APIs, storage contracts, versioning model, benchmarks, debugging tools, and reliability guarantees that make data access consistent across current and future training frameworks. You will begin as the primary technical owner for dataset reads, working directly in the code while aligning researchers, training framework owners, storage teams, and infrastructure partners around a durable platform. The problem is deceptively hard at frontier scale: make enormous, heterogeneous datasets easy to consume, correct across distributed workers, observable when something goes wrong, and flexible enough to support pretraining, reinforcement learning, and multimodal training. In this role, you will Design and build a unified dataset read platform for multiple current and future training frameworks. Define dataset APIs, storage-format expectations, registration/versioning, and migration paths that make data access reproducible and maintainable. Build reliability into the read path, including stateful iteration, caching, fast restart, recovery, and clear operational contracts. Build terminal and web-based visualizers that let teams inspect text, multimodal, and reinforcement learning data late

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 Performance Engineer, you’ll drive efficiency improvements across our distributed training stack. You’ll analyze large-scale training runs, identify utilization gaps, and design optimizations that push the boundaries of throughput and uptime. This role blends deep systems understanding with practical performance engineering — analyzing GPU kernel performance, collective communication throughput, investigating I/O bottlenecks, and sharding our models so we can train them at massive scale. You’ll help ensure that our clusters are running at peak performance, enabling OpenAI to train larger, more capable models with the same compute budget. This role is based in San Francisco, CA. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees. In this role, you will: Profil