Technical Deployment Lead, Forward Deployed Engineering (fde)- Platform

OpenAI OpenAI · AI Frontier · San Francisco, CA · Model Deployment for Business

This role is a founding Technical Deployment Lead (TDL) for the FDE Platform team at OpenAI. The primary focus is on making early design partner deployments successful, from scoping to production adoption and demonstrated value. The role involves driving alignment across OpenAI and customer stakeholders, managing delivery plans, ensuring enterprise constraints (security, auditability, infra) are handled, and converting learnings into actionable improvements. Success is measured by delivered outcomes, adoption in critical workflows, and platform reliability.

What you'd actually do

  1. Define pilot scope and success criteria: Partner with customer sponsors and technical leads to translate goals into a concrete plan, measurable outcomes, and clear acceptance criteria.
  2. Own the delivery plan across work streams: Build and run integrated milestones, dependencies, and execution rhythms across Applied, platform engineers, and customer teams.
  3. Drive stakeholder alignment and decision-making: Lead internal and external working sessions, keep tradeoffs explicit, unblock decisions, and escalate crisply when needed.
  4. Ensure enterprise readiness from day one: Pressure-test security posture, permissions and access boundaries, audit-ability, and deployment/infra requirements as part of the delivery plan.
  5. Manage production adoption and value realization: Drive onboarding, enablement, and change management so deployments land in real workflows and deliver measurable impact.

Skills

Required

  • 5+ years leading complex, customer-facing technical delivery
  • Deeply credible with senior technical stakeholders
  • Strong instincts for enterprise security and governance
  • Ops-first background (e.g., platform delivery leadership, technical program/delivery leadership, product/engineering operations)
  • Communicate with executive presence

Nice to have

  • architectures
  • reason about enterprise deployment constraints
  • go in the weeds when required
  • driving execution through matrixed teams
  • make tradeoffs legible
  • keep teams focused on the critical path under pressure

What the JD emphasized

  • enterprise constraints
  • enterprise readiness
  • enterprise security and governance

Other signals

  • customer deployments
  • enterprise readiness
  • product shaping
  • shipped software