Jobs at OpenAI

Build and operate backend systems, workflow tooling, and data pipelines for lawful data access requests. Implement least-privilege access, audit trails, data minimization, and approval gates. Partner with Legal and Operations to translate requirements into secure, auditable, and operator-friendly systems. Own production reliability, testing, observability, and incident response while defining reusable privacy infrastructure.

Lead post-sales enablement for OpenAI products, including ChatGPT Enterprise and Agents. Design and deliver onboarding, workshops, advanced training, executive briefings, and adoption programs for business and technical audiences. Drive activation, sustained usage, product expansion, and measurable business value across enterprise customers. Develop reusable training assets and playbooks, gather customer feedback, identify adoption patterns, and collaborate with Sales, Solution Architects, Delivery Leads, and product teams.

Lead end-to-end customer deployments of frontier AI models, from discovery and system design through production rollout. Build full-stack systems, contribute production code, guide customer adoption, manage delivery trade-offs, and create reusable tools and playbooks. Collaborate with customer engineering teams and internal Product, Research, Security, GRC, Partnerships, and GTM teams. Use field feedback and evaluations to improve products and model roadmaps.

Provide premium customers with hands-on technical troubleshooting and end-to-end ownership for complex API, integration, authentication, performance, and production issues. Analyze logs and system behavior, coordinate incident response, communicate with technical and executive stakeholders, monitor customer integrations, develop runbooks, lead postmortems, and translate recurring problems into product, tooling, monitoring, and automation improvements.

Partner with startups to identify high-impact Codex use cases, build AI coding workflows and integrations, resolve technical issues, and drive sustained adoption. Lead technical talks, demos, workshops, hackathons, and developer programs. Create reusable code examples, guides, and tools, while translating customer feedback into improvements for OpenAI’s Product, Research, and Engineering teams.

Owns technical strategy and customer outcomes for enterprise AI adoption across ChatGPT Enterprise, the OpenAI API, Codex, and agentic solutions. Leads executive discovery, AI architecture, technical evaluations, prototypes, production-readiness planning, adoption roadmaps, and measurable business impact. Partners with sales, engineering, deployment, security, product, research, and implementation teams while advising CTO, CIO, CISO, and engineering stakeholders.

Leads OpenAI’s Applied AI Architect team across Europe, developing technical strategy and operating models for strategic enterprise customers. Oversees customer journeys from discovery through production adoption, coaches senior architects, manages resources, advises executives, and coordinates Sales, Product, Engineering, Research, Security, Legal, Privacy, and deployment specialists. Ensures secure, scalable architectures, responsible AI adoption, measurable customer outcomes, portfolio health, and expansion opportunities.

Deliver hands-on GenAI implementations for international government customers, from identifying mission needs through architecture, prototyping, evaluation, production readiness, adoption, and handoff. Partner with agencies, technical teams, systems integrators, cloud providers, and senior stakeholders while addressing privacy, data residency, security, identity, procurement, and regulated-environment requirements. Build applications with OpenAI technologies, contribute developer resources, share best practices, provide product feedback, and manage multiple concurrent customer engagements.

Design, build, evaluate, and deploy AI-powered software development workflows using Codex. Partner with engineering organizations to move from prototypes to reliable production systems, improve developer adoption and productivity, and address model behavior, integrations, security, reliability, observability, cost, and operational readiness. Lead technical workshops, diagnose implementation challenges, develop evaluation systems, and translate deployment insights into product feedback, reusable architectures, and technical resources.

Lead end-to-end deployment of frontier AI models for strategic customers, from discovery and system design through production rollout. Build full-stack systems, contribute production code, guide customer adoption, manage delivery trade-offs, and codify reusable tools and playbooks. Partner with customer engineering, Product, Research, Security, GRC, Partnerships, and GTM teams while providing feedback to improve models and product roadmaps. Professional fluency in Spanish and English is required, with travel up to 50%.

Build backend infrastructure and customer-facing workflows for AI agents in secure enterprise cloud environments. Develop Go services and APIs, cloud provisioning, orchestration for long-running parallel tasks, integrations with developer tools, and security controls such as permissions, credential handling, isolation, and auditability. Own production quality through testing, rollouts, observability, performance, and reliability while collaborating with customers, frontend, infrastructure, and security teams.

Own the technical strategy and customer journey for a portfolio of education institutions adopting OpenAI solutions. Lead discovery, architecture design, technical evaluations, prototypes, adoption roadmaps, governance, deployment readiness, and value realization. Build relationships with executive, academic, research, and technical stakeholders while coordinating specialist teams. Translate education needs into responsible AI use cases and reusable architectures, track adoption and customer impact, and provide feedback to Product, Engineering, and Research.

As a Software Engineer in Infrastructure Reliability, you'll design and build resilient systems, optimize performance, improve automation, and collaborate with teams to enhance infrastructure reliability.

Develop and scale new LLM architectures, run and analyze training experiments, debug and optimize model and compute performance, and contribute to training and inference infrastructure. Work collaboratively to improve model intelligence, efficiency, and capabilities. Role is hybrid, based in London with relocation assistance.

Design and build distributed systems for large-scale AI training, focusing on performance, stability, monitoring, and debugging of infrastructure.

Design, operate, troubleshoot, and automate secure enterprise routing, switching, wireless, WAN, and cloud connectivity. Balance platform architecture, standards, lifecycle planning, and automation with incident response, change safety, and operational delivery. Reduce recurring reactive work through software, APIs, Infrastructure-as-Code, Git workflows, testing, and CI/CD.

Provide frontline IT support by troubleshooting hardware, software, and network issues, improve support processes, and participate in on-call rotation.

As a Software Engineer on the Storage Infrastructure team, you will design, build, and operate systems for managing large-scale research data securely and reliably across multiple regions.

Research and develop novel safety mitigations for frontier AI systems: measure emerging risks, build and refine evaluations, design red-teaming pipelines, set research directions, and collaborate across domains (misalignment, cybersecurity, biology) to ensure enforceable, scalable, and effective safety stacks.

Develop and optimize large-scale compute systems for AI workloads, improving infrastructure reliability and performance across various layers of the stack.