Applied AI Engineer, Codex

OpenAIs Applied AI Engineering team helps organizations turn frontier AI capabilities into safe reliable and high-impact production systems. For software engineering organizations this means helping customers adopt Codex and other OpenAI capabilities across the software development lifecycletransforming how teams plan build test review and deliver software.

We work directly with engineering leaders and hands-on developers to identify high-value opportunities design and implement AI-powered development workflows and scale what works across engineering organizations. We turn lessons from these deployments into better products reusable architectures and technical patterns that help developers everywhere get more value from Codex.

As an Applied AI Engineer focused on Codex you will partner directly with leading engineering organizations to design build and deploy AI systems that transform how software is developed. You will combine deep technical judgment hands-on engineering and customer leadership to take ambitious ideas from workflow and use-case selection through prototyping evaluation production rollout and scaled adoption.

You will work alongside engineering teams to build advanced AI coding workflows integrations automations and evaluation systemsoften using Codex itself as part of your development process. You will help customers make technical decisions involving model behavior agentic workflows developer environments security reliability evaluation and operational readiness while ensuring deployments translate into measurable improvements in engineering productivity and software delivery.

You will work closely with OpenAI Product Research Engineering Security Sales and the broader Codex organization translating real-world deployment experience into high-signal product and model feedback. Success is measured by production systems sustained developer adoption and meaningful improvements to how engineering organizations build software not simply successful demonstrations or enablement activity.

This role is based in our London office. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.

• Partner directly with engineering leaders and hands-on developers to identify high-value opportunities for Codex and translate them into technical architectures implementation plans evaluation strategies and measurable success criteria.

• Design build and deploy AI-powered software development workflows that improve how engineering teams plan write test review debug and deliver software.

• Work hands-on in code to build prototypes evaluation harnesses reference implementations integrations workflow automations and production acceleratorsoften using Codex as part of your own development process.

• Help customers progress from promising experiments to reliable production workflows sustained developer adoption and scaled impact across engineering organizations.

• Design systematic approaches for evaluating AI coding systems using representative software engineering tasks automated graders production signals and developer feedback.

• Make sound technical decisions across models agents tools developer environments integrations reliability observability latency cost safety security and operational readiness.

• Diagnose complex implementation challenges reproduce failures test hypotheses and drive technical blockers toward resolution.

• Lead technical deep dives workshops and hands-on enablement that help engineering teams understand and adopt advanced AI coding workflows effectively and safely.

• Gather high-fidelity insights from real-world Codex deployments and translate them into clear product proposals model feedback and technical requirements for OpenAI Product Research and Engineering teams.

• Create reusable architectures tooling examples guides and technical patterns including contributions to resources such as the OpenAI Cookbookthat accelerate future Codex deployments.

• Influence customer engineering strategy by helping technical leaders understand how AI coding systems can reshape their software development lifecycle engineering practices and organizational workflows.

• Have a demonstrated track record of designing building and delivering software or AI systems in enterprise environments including taking systems from prototype to production. Relevant backgrounds may include applied AI or ML engineering forward-deployed…