Technical Deployment Lead, Forward Deployed Engineering - Zurich

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the Role As a Technical Deployment Lead (TDL), you will define how OpenAI delivers complex systems to customers. You will own how they are built, shipped, and adopted. You’ll translate business outcomes into a technical plan, run day-to-day execution across FDEs, Researchers, and Customer Engineers, and partner with customer teams to ensure delivery supports their goals. This is not a management role, however you'll own delivery end-to-end: embedding with customers to map workflows and success criteria, ensuring components ship on time, and leading readiness and change management for adoption. You’ll track progress, manage dependencies, make sequencing decisions, and drive 0→1 prototypes through MVP and scale. You will also share field insights with Product and Research to guide roadmap and priorities. Success will be measured first and foremost by impact - deployments that deliver measurable value against customer goals, drive adoption, and become critical to their workflows. Additional measures of success include delivery reliability (milestones hit, low reopen/churn), operating leverage (patterns reused across deployments), judgment under pressure, and product impact (field signal that shifts roadmaps/architectures). This is a high-trust, high-autonomy role. Success requires deep technical project management expertise, extreme ownership of outcomes, and an ability to immerse in customer workflows and partner with customer teams to solve complex engineering problems at pace. This role is based in Zurich. We use a hybrid model of 3 days in office and offer relocation assistance. Travel up to 50% is required. In this role, you will: - Own the technical delivery plan for multiple interdependent workstreams. Translate business objectives into a roadmap with milestones, dependencies, and acceptance criteria. - Run day-to-day engineering execution. Track and drive delivery across OpenAI FDE and customer teams. Keep progress unblocked and sequenced. Make real-time trade-offs on scope and priority to protect the critical path. - Embed with customer teams to land production deployments and drive adoption. Map workflows, shape tools/integrations, and translate requirements into a delivery plan. Lead onboarding, adoption, and change management. - Partner with Product and Research so platform components and research workstreams land in time to support deployment goals. - Codify solution patterns and evals. Extract reusable patterns and package field signals to improve product and models. - Own value cases and ROI. Set impact hypotheses, baselines, and KPIs; run pre-/post-deployment measurement and report to exec sponsors. You’ll thrive in this role if you: - Bring 7+ years of customer‑facing technical delivery leadership. - Track record of successfully leading large, complex, high-stakes customer engagements where customer outcomes depended on tight coordination and fast decision making, ideally involving AI. - Excel in high ambiguity environments. Know how to simplify complex and dynamic work. - Move fluidly between system level understanding and execution level detail; can dive into customer workflows/data, map constraints, sketch architectures and move ambiguous problems to shipped systems. - Think strategically and pattern-match. Able to step back from execution detail, recognise broader trends across deployments, and connect customer needs to scalable, reusable solutions. - Have strong technical fluency and sharp sequencing instincts. Confident discussing technical details, pressure-testing architectures, and making trade-offs. - Have shipped AI/LLM systems. You understand solution patterns, integration basics, and production pitfalls. - You’re a translator with executive presence. You make complex technical trade-offs legible to business leaders and convert strategy into day-to-day technical execution. - Enjoy being onsite with customers to accelerate delivery (often 25-50%, sometimes higher). - Have expertise in at least one major sector (e.g., healthcare, energy, financial services, semiconductors, IT) to elevate solution framing and credibility. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, na

7+ years of customer-facing technical delivery leadership. Track record leading large, complex, high-stakes customer engagements where customer outcomes depended on tight coordination and fast decision making, ideally involving AI. Ability to operate in high ambiguity environments, simplify complex problems, and translate between system-level and execution-level details. Experience shipping AI/LLM systems, understanding solution patterns, integration basics, and production pitfalls. Strong technical fluency, sequencing instincts, and the ability to discuss technical details with executive stakeholders. Willingness to be onsite with customers (often 25-50%). Experience with at least one major sector (e.g., healthcare, energy, financial services, semiconductors, IT) to elevate solution framing.

Own the technical delivery plan for multiple interdependent workstreams, translating business objectives into a roadmap with milestones, dependencies, and acceptance criteria. Run day-to-day engineering execution, track and drive delivery across OpenAI FDE and customer teams, keep progress unblocked, and manage scope/priorities. Embed with customer teams to land production deployments, map workflows, shape tools/integrations, and lead onboarding, adoption, and change management. Partner with Product and Research to ensure platform components and research workstreams land on time. Codify solution patterns and field signals to improve product and models. Own value cases and ROI, set impact hypotheses and KPIs, and run pre-/post-deployment measurement for executive reporting.