Deployment Lead, Semiconductors- SF

About the Team

OpenAI’s Forward Deployed Engineering (FDE) team turns research breakthroughs into production-grade systems. We embed deeply with customers to solve high-leverage problems and act as the delivery engine for our most complex large-scale engagements. We move quickly from prototype to production and surface reusable patterns that shape our platform. We operate at the intersection of deployment and development – working closely with OpenAI Research, Product and Partnerships.

About the Role

As a Deployment Lead, you will define how OpenAI delivers complex systems to Semiconductor customers. You will own how solutions are scoped, built, shipped, and adopted across high-value engineering workflows such as RTL design, verification, and physical implementation. 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.

You will focus on the semiconductor vertical to deploy next-generation AI capabilities. You will 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 San Francisco. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel between 25-50% is required.

In this role, you will:

Own the technical delivery plan for multiple interdependent work streams, translating customer objectives into a roadmap with milestones, dependencies, and acceptance criteria.

Run day-to-day engineering execution by tracking and driving 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 Semiconductor customer teams to land production deployments and drive adoption. Map workflows, shape tools/integrations, and translate requirements into a delivery plan.

Shape production deployments that integrate with customer infrastructure, data systems, and engineering toolchains, including export-controlled environments.

Partner with Product and Research so platform components and research work streams 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.

Help define how OpenAI engages Semiconductor customers.

You might thrive in this role if you:

Bring 7+ years of customer‑facing technical delivery leadership.

Have deep expertise in Semiconductor workflows, including RTL design, verification, EDA tooling, and physical implementation.

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, recognize broader trends across deployments, and connect customer needs to scalable, reusable solutions.