About this role
Organizations often struggle to turn frontier artificial intelligence capabilities into safe, reliable, and high-impact production systems amidst complex existing architectures and diverse data environments. OpenAI needs an Applied AI Engineer to help digital native companies design, build, and deploy AI-powered products that bridge early experimentation with measurable business outcomes.
Working alongside customer engineering and product teams, the person in this role will write and debug code, build evaluation systems, resolve complex integrations, and guide technical decisions involving model behavior, reliability, latency, and cost. Success relies on achieving sustained production adoption while channeling deployment lessons back into OpenAI's broader product evolution.
What you will do
- Partner directly with Digital Native customers to identify high-value opportunities and translate them into technical architectures, implementation plans, evaluation strategies, and measurable success criteria.
- Design, build, and deploy AI systems that solve important customer problems and produce measurable business outcomes.
- Work hands-on in code to build prototypes, evaluation harnesses, reference implementations, integrations, and production accelerators.
- Make sound technical decisions across models, agents, retrieval, tools, data, reliability, observability, latency, cost, safety, security, and governance.
- Diagnose complex implementation challenges, reproduce failures, test hypotheses, and drive blockers toward resolution.
- Help customers progress from promising prototypes to reliable production systems, sustained adoption, and scaled impact.
- Partner closely with customer engineering teams and internal product, research, engineering, security, and go-to-market teams to translate deployment experience into product feedback.
- Create reusable architectures, tooling, playbooks, and technical guidance that accelerate future enterprise deployments.
What you need
- Demonstrated track record of designing, building, and delivering AI or machine-learning systems in enterprise environments, including taking systems from prototype to production.
- Ability to point to substantial personal contributions in code, architecture, evaluation, debugging, or production engineering.
- High proficiency in Python and comfort working across an AI application stack.
- Understanding of how to evaluate AI systems systematically using representative data, graders, production signals, and human judgment.
- Experience navigating enterprise production requirements such as integrations, reliability, observability, security, privacy, data governance, performance, and cost.
- Clear communication skills that bridge hands-on engineers, technical leaders, security teams, product leaders, and executives.
Nice to have
- Experience with JavaScript, TypeScript, or another relevant language
Benefits
- Relocation assistance to new employees
Skills and tech stack
Questions candidates ask
Where is this job located and what is the remote policy?
This role is based in London. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.
What will I actually be working on day-to-day?
You will partner directly with Digital Native companies to design, build and deploy AI-powered products and systems. Working alongside customer product and engineering teams, you will take ideas from early experimentation through evaluation, production launch and scale.
What programming languages and technical skills are required?
You must be highly proficient in Python and comfortable working across an AI application stack, with experience in JavaScript, TypeScript, or another relevant language being valuable. You will also need to demonstrate substantial personal contributions in code, architecture, evaluation, debugging, or production engineering.
Do I need prior industry-specific experience or familiarity with OpenAI products?
Experience in a particular industry or with OpenAI products is not required. You will thrive if you learn quickly, challenge assumptions constructively, and collaborate with humility.