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OpenAI's Applied AI Engineering team helps organizations deploy frontier AI capabilities into safe, reliable, and high-impact production systems. This role focuses on Codex, OpenAI's AI coding system, and involves partnering directly with leading engineering organizations to design, build, and deploy AI systems that transform how software is developed.
As an Applied AI Engineer, 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 systems—often using Codex itself as part of your development process.
Key responsibilities include:
- Partnering with engineering leaders and developers to identify high-value opportunities for Codex and translate them into technical architectures, implementation plans, and measurable success criteria
- Designing, building, and deploying AI-powered software development workflows that improve how teams plan, write, test, review, debug, and deliver software
- Working hands-on in code to build prototypes, evaluation harnesses, reference implementations, integrations, and production accelerators
- Helping customers progress from experiments to reliable production workflows and scaled impact
- Designing systematic approaches for evaluating AI coding systems using representative tasks, automated graders, and production signals
- Making sound technical decisions across models, agents, tools, environments, reliability, security, and operational readiness
- Diagnosing complex implementation challenges and driving technical blockers toward resolution
- Leading technical deep dives, workshops, and hands-on enablement for engineering teams
- Gathering insights from real-world deployments and translating them into product proposals and technical requirements
- Creating reusable architectures, tooling, examples, and technical patterns
- Influencing customer engineering strategy by helping leaders understand how AI coding systems can reshape their development lifecycle
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.
The role is based in the London office with a hybrid work model of 3 days in the office per week. Relocation assistance is offered to new employees.
REQUIREMENTS:
- Demonstrated track record of designing, building, and delivering software or AI systems in enterprise environments, including taking systems from prototype to production. Relevant backgrounds include applied AI/ML engineering, forward-deployed engineering, software engineering, developer tooling, customer engineering, solutions architecture, or technical consulting
- Substantial personal contributions in code, architecture, evaluation, debugging, integrations, or production engineering—not only program management, enablement, or stakeholder management
- 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 how AI can improve developer productivity and software engineering workflows
- Ability to build high-signal prototypes, integrations, automations, and production solutions
- Understanding of how to evaluate AI coding systems systematically, including designing representative tasks, automated evaluations, and production signals
- 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
- Clear communication with hands-on engineers, engineering leaders, security teams, product leaders, and executives
- Comfort leading technical workshops and hands-on sessions
- High agency, strong technical judgment, and end-to-end ownership in ambiguous and rapidly evolving environments
- Ability to learn quickly, challenge assumptions constructively, and collaborate with humility
- Fluent English
