SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
OpenAI's Applied AI Engineering team partners with enterprise organizations to transform frontier AI capabilities into safe, reliable, and high-impact production systems. This role sits at the intersection of technical depth and customer impact, working directly with leading organizations to design, build, and deploy AI systems that deliver measurable business outcomes.
As an Applied AI Engineer, you will combine deep technical judgment, hands-on engineering, and customer leadership to shepherd ambitious AI initiatives from use-case selection and architecture through prototyping, evaluation, production launch, and scale. You'll write and debug code, build evaluation systems, resolve complex integrations, and guide decisions spanning model behavior, reliability, latency, cost, safety, security, governance, and operational readiness. Success is measured by production systems, sustained adoption, and meaningful customer impact.
Key responsibilities include: partnering directly with enterprise customers to identify high-value opportunities and translate them into technical architectures and implementation plans; designing and building AI systems that solve important problems with measurable outcomes; working hands-on in code to build prototypes, evaluation harnesses, reference implementations, and production accelerators; making sound technical decisions across the full AI stack; diagnosing complex implementation challenges and driving blockers to resolution; helping customers progress from prototype to reliable production systems; collaborating with customer engineering teams and OpenAI's product, research, engineering, and security teams to translate deployment experience into product feedback; and creating reusable architectures, tooling, and playbooks that accelerate future deployments.
Ideal candidates have a demonstrated track record of designing, building, and delivering AI/ML systems in enterprise environments, including taking systems from prototype to production. Relevant backgrounds include applied AI/ML engineering, forward-deployed engineering, software engineering, customer engineering, solutions architecture, or technical consulting. You should have substantial personal contributions in code, architecture, evaluation, debugging, or production engineering. High proficiency in Python is required, with comfort across the AI application stack; experience with JavaScript, TypeScript, or other relevant languages is valuable. You understand how to systematically evaluate AI systems using representative data, graders, production signals, and human judgment. You've navigated enterprise production requirements such as integrations, reliability, observability, security, privacy, data governance, performance, and cost. You can connect technical decisions to customer workflows, adoption, and measurable business outcomes, and communicate with clarity across engineers, leaders, security teams, and executives. You bring high agency, strong technical judgment, and end-to-end ownership in ambiguous environments, learn quickly, challenge assumptions constructively, and collaborate with humility.
The role is based in London with a hybrid work model of 3 days in the office per week. Relocation assistance is offered to new employees.
