2 months ago
London, United KingdomSenior
Responsibilities
- Partner with enterprise 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 customer problems and produce measurable business outcomes.
- Write code and build prototypes, evaluation harnesses, reference implementations, integrations, and production accelerators.
- Make technical decisions across models, agents, retrieval, tools, data, reliability, observability, latency, cost, safety, security, and governance.
- Diagnose implementation challenges, reproduce failures, test hypotheses, and resolve blockers.
- Help customers move from prototypes to reliable production systems, sustained adoption, and scaled impact.
- Collaborate with customer engineering teams and OpenAI Product, Research, Engineering, Security, and go-to-market teams.
- Create reusable architectures, tooling, playbooks, and technical guidance for future enterprise deployments.
- Translate deployment experience into high-signal product feedback.
Requirements
- Demonstrated experience designing, building, and delivering AI or machine-learning systems in enterprise environments from prototype through production.
- Substantial personal contributions in coding, architecture, evaluation, debugging, or production engineering.
- High proficiency in Python and comfort working across an AI application stack.
- Experience systematically evaluating AI systems with representative data, graders, production signals, and human judgment.
- Experience with enterprise production requirements including integrations, reliability, observability, security, privacy, data governance, performance, and cost.
- Ability to connect technical decisions to customer workflows, adoption, and measurable business outcomes.
- Clear and credible communication with engineers, technical leaders, security teams, product leaders, and executives.
- High agency, strong technical judgment, and end-to-end ownership in ambiguous environments.
- Experience with JavaScript, TypeScript, or another relevant language is valuable but not required.
- Backgrounds in applied AI or ML engineering, forward-deployed engineering, software engineering, customer engineering, solutions architecture, or technical consulting are relevant.
- Experience in a particular industry or with OpenAI products is not required.
Benefits
- Hybrid work model requiring 3 days in the London office per week.
- Relocation assistance is offered to new employees.
- Reasonable accommodations are available for applicants with disabilities.
Tech Stack
Categories
AI ApplicationsForward 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.