Manager, Technical Deployment Leads (tdl), Forward Deployed Engineering (fde)

OpenAI OpenAI · AI Frontier · San Francisco, CA · Forward Deployed Engineering

Manager for Technical Deployment Leads (TDLs) in the Forward Deployed Engineering (FDE) team, responsible for leading teams that partner with customers to turn research breakthroughs into production systems. The role involves owning end-to-end delivery outcomes, managing high-stakes customer deployments, and translating business needs into technical delivery plans. Success is measured by team shipping consistency, signal delivery to Research and Product, and the durability of the team and delivery model.

What you'd actually do

  1. Lead and grow a team of TDLs delivering production systems with frontier models
  2. Own end-to-end delivery outcomes through clarity, speed, tight coordination, and technical quality
  3. Codify what works into tools, playbooks, and roadmap inputs that create leverage
  4. Notice early indicators and raise them with urgency, whether in product behavior, customer environments, or delivery practices
  5. Use judgement to distinguish what requires action and what does not

Skills

Required

  • 8+ years of customer-facing technical delivery leadership
  • 2+ years managing high-performing technical delivery, program management, or customer engineering teams
  • Led high-pressure technical projects from prototype to production
  • Simplify complex work and make fast, sound decisions under pressure
  • Elevate team performance through clarity, not process
  • Operate with urgency in ambiguous or evolving environments
  • Build deep trust with your team by modeling calm, focus, and judgment when it matters most
  • Built and scaled an operating model for delivery: staffing, cadence, artifacts, risk management, and clear ownership across teams
  • Technical fluency and sharp sequencing judgment
  • Confident pressure-testing architectures and trade-offs across security, reliability, latency, cost, and scope

Nice to have

  • customer delivery
  • production systems
  • technical delivery leadership
  • managing technical teams

What the JD emphasized

  • high-stakes, ambiguous customer deployments
  • technical and business value outcomes end to end
  • operate under pressure
  • learn from the field
  • translate business outcomes into technical delivery plans
  • run day-to-day execution
  • ensure delivery supports their goals
  • scope, sequencing, risk management, and communication
  • deployments drift or stakes spike
  • reset the plan, unblock teams, and protect customer trust
  • how OpenAI is trusted by the customers closest to our deployment work
  • how consistently your team ships
  • how clearly you deliver signal to Research and Product
  • how durable your team and delivery model prove to be
  • 8+ years of customer-facing technical delivery leadership
  • 2+ years managing high-performing technical delivery, program management, or customer engineering teams
  • led high-pressure technical projects from prototype to production
  • Simplify complex work and make fast, sound decisions under pressure
  • Operate with urgency in ambiguous or evolving environments
  • Build deep trust with your team by modeling calm, focus, and judgment when it matters most
  • built and scaled an operating model for delivery: staffing, cadence, artifacts, risk management, and clear ownership across teams
  • technical fluency and sharp sequencing judgment
  • Confident pressure-testing architectures and trade-offs across security, reliability, latency, cost, and scope

Other signals

  • customer delivery
  • production systems
  • technical delivery leadership
  • managing technical teams