Applied AI Engineer, Codex
Remote • London, UK • FullTime
Posted 3d ago
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
Applied AI Engineer
About the job
OpenAI's Applied AI Engineering team empowers organizations to leverage frontier AI capabilities, specifically Codex, to enhance the software development lifecycle. 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. This involves combining deep technical judgment, hands-on engineering, and customer leadership to guide ambitious ideas from concept through production and scaled adoption. You will work alongside engineering teams to build advanced AI coding workflows, integrations, and evaluation systems, often using Codex itself in the development process. Your role will be crucial in helping customers make informed technical decisions regarding model behavior, agentic workflows, developer environments, security, reliability, and operational readiness, ensuring measurable improvements in engineering productivity and software delivery.
Responsibilities
- Partner with engineering leaders and developers to identify high-value opportunities for Codex and translate them into technical architectures, implementation plans, and success criteria.
- Design, build, and deploy AI-powered software development workflows to improve planning, writing, testing, reviewing, debugging, and delivery of software.
- Build prototypes, evaluation harnesses, reference implementations, integrations, workflow automations, and production accelerators, often using Codex in your own development process.
- Help customers transition from experiments to reliable production workflows, sustained developer adoption, and scaled impact.
- Design systematic approaches for evaluating AI coding systems using representative 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 enablement sessions to help engineering teams understand and adopt advanced AI coding workflows effectively and safely.
- Gather insights from real-world Codex deployments and translate them into product proposals and feedback for OpenAI Product, Research, and Engineering teams.
- Create reusable architectures, tooling, examples, guides, and technical patterns to accelerate future Codex deployments.
- Influence customer engineering strategy by educating technical leaders on how AI coding systems can reshape their software development lifecycle and organizational workflows.
Requirements
- Demonstrated track record of designing, building, and delivering software or AI systems in enterprise environments, from prototype to production.
- Substantial personal contributions in code, architecture, evaluation, debugging, integrations, or production engineering.
- High proficiency in Python and comfort working across modern software development environments.
- Experience with JavaScript, TypeScript, or another relevant language is valuable.
- Active user of AI coding tools with a strong point of view on AI's impact on developer productivity and software engineering workflows.
- Experience building high-signal prototypes, integrations, automations, and production solutions with AI coding systems.
- Understanding of how to systematically evaluate AI coding systems, including designing representative tasks, automated evaluations, and feedback mechanisms.
- Experience navigating enterprise production requirements such as 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.
Benefits
- Hybrid work model (3 days in office per week)
- Relocation assistance for new employees