8 hours ago
London, United KingdomSenior
Responsibilities
- Partner with engineering leaders and developers to identify Codex opportunities and define architectures, implementation plans, evaluation strategies, and success criteria.
- Design, build, and deploy AI-powered workflows for planning, writing, testing, reviewing, debugging, and delivering software.
- Develop prototypes, evaluation harnesses, reference implementations, integrations, workflow automations, and production accelerators.
- Help customers move from experiments to reliable production workflows, sustained adoption, and scaled organizational impact.
- Create systematic evaluations using representative software engineering tasks, automated graders, production signals, and developer feedback.
- Make technical decisions involving models, agents, tools, developer environments, reliability, observability, latency, cost, safety, security, and operational readiness.
- Diagnose implementation challenges, reproduce failures, test hypotheses, and resolve technical blockers.
- Lead technical deep dives, workshops, and hands-on enablement sessions for engineering organizations.
- Translate deployment insights into product proposals, model feedback, technical requirements, reusable architectures, tooling, examples, and guides.
- Influence customer engineering strategy and collaborate with Product, Research, Engineering, Security, Sales, and the broader Codex organization.
Requirements
- Demonstrated experience designing, building, and delivering software or AI systems in enterprise environments from prototype through production.
- Substantial hands-on contributions in code, architecture, evaluation, debugging, integrations, or production engineering.
- High proficiency in Python and comfort working across modern software development environments; JavaScript, TypeScript, or another relevant language is valuable.
- Active use of AI coding tools and a strong perspective on improving developer productivity and software engineering workflows.
- Ability to evaluate AI coding systems systematically through representative tasks, automated evaluations, production signals, and developer feedback.
- Experience navigating enterprise requirements including developer tooling integrations, reliability, observability, security, privacy, data governance, performance, and cost.
- Ability to connect technical decisions to developer workflows, adoption, engineering productivity, and measurable business outcomes.
- Clear and credible communication with engineers, engineering leaders, security teams, product leaders, and executives.
- Comfort leading technical workshops and hands-on sessions.
- High agency, strong technical judgment, end-to-end ownership, rapid learning, constructive challenge, and collaborative humility.
- Fluent English communication.
- Prior OpenAI product experience is not required.
Benefits
- London-based hybrid work model requiring three days in the office per week.
- Relocation assistance is available to new employees.
- OpenAI is an equal opportunity employer and provides reasonable accommodations for applicants with disabilities.
Tech Stack
Categories
Forward Deployed
About OpenAI
OpenAI builds and deploys large-scale AI models and tools—including ChatGPT, GPT-4–class models, DALL·E, and Whisper—sold via APIs and enterprise subscriptions to developers and businesses. It monetizes through usage-based API pricing and ChatGPT Plus/Team/Enterprise, and also reaches customers via Microsoft’s Azure OpenAI Service. Founded in 2015 and headquartered in San Francisco, it operates as a private partnership.