Technical Deployment Lead - Tokyo

OpenAI OpenAI · AI Frontier · Tokyo, Japan · Model Deployment for Business

This role is a founding Technical Deployment Lead at OpenAI, focused on partnering with customers to deliver complex AI systems. The role involves defining delivery processes, translating business needs into technical plans, managing execution across engineering and research teams, and ensuring customer adoption and value realization. It requires deep technical project management, ownership, and the ability to work in ambiguous, high-autonomy environments, with a focus on shipping AI/LLM systems to customers and codifying reusable patterns from field insights.

What you'd actually do

  1. Own the technical delivery plan for multiple interdependent workstreams. Translate business objectives into a roadmap with milestones, dependencies, and acceptance criteria.
  2. 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.
  3. 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.
  4. Partner with Product and Research so platform components and research workstreams land in time to support deployment goals.
  5. Codify solution patterns and evals. Extract reusable patterns and package field signals to improve product and models.
  6. Own value cases and ROI. Set impact hypotheses, baselines, and KPIs; run pre-/post-deployment measurement and report to exec sponsors.

Skills

Required

  • 7+ years of customer-facing technical delivery leadership
  • Successfully leading large, complex, high-stakes customer engagements
  • High ambiguity environments
  • System level understanding and execution level detail
  • Strategic thinking and pattern matching
  • Strong technical fluency and sharp sequencing instincts
  • Shipped AI/LLM systems
  • Translator with executive presence
  • Onsite with customers
  • Expertise in at least one major sector (e.g., healthcare, energy, financial services, semiconductors, IT)

Nice to have

  • AI/LLM systems understanding
  • solution patterns
  • integration basics
  • production pitfalls

What the JD emphasized

  • customer delivery
  • production systems
  • translate business outcomes into technical plan
  • drive 0->1 prototypes through MVP and scale
  • field insights to guide roadmap
  • impact - deployments that deliver measurable value
  • drive adoption
  • critical to their workflows
  • reusable patterns
  • package field signals to improve product and models
  • shipped AI/LLM systems

Other signals

  • customer delivery
  • production systems
  • translate business outcomes into technical plan
  • drive 0->1 prototypes through MVP and scale
  • field insights to guide roadmap
  • impact - deployments that deliver measurable value
  • drive adoption
  • critical to their workflows
  • reusable patterns
  • package field signals to improve product and models
  • shipped AI/LLM systems