AI Deployment Engineer, Startups

OpenAI OpenAI · AI Frontier · Singapore · Go To Market

AI Deployment Engineer focused on working with strategic startup customers to optimize their AI systems, prototype prompts/agents, and translate customer feedback into reproducible evaluations and product improvements for OpenAI's research and products. The role involves deep technical engagement, understanding system behavior, and building relationships within the startup ecosystem.

What you'd actually do

  1. Work directly with strategic startup customers to understand critical workflows, uncover failure modes, and identify high-impact opportunities for improvement.
  2. Prototype and iterate on prompts, agents, and workflow designs to better understand system behavior and unlock customer value.
  3. Synthesize and deliver valuable feedback to the Product and Research teams, turning real usage patterns into clear, reproducible evals, benchmarks, and technical artifacts that improve model and product quality and ensure customer-grounded learnings influence roadmap and model development.
  4. Build repeatable tools, patterns, and evaluation approaches that raise the quality bar across multiple use cases.
  5. Operate with strong judgment in ambiguous environments, balancing immediate technical problem-solving with longer-term system improvement.

Skills

Required

  • strong software engineering & AI fundamentals
  • experience shipping production systems end-to-end
  • familiarity with model training pipelines and reinforcement learning
  • experience building AI applications, agents, or evaluation systems
  • reasoning clearly about model behavior in complex workflows
  • working directly with highly technical users
  • translating user challenges into concrete technical signals
  • prototyping
  • debugging
  • evaluation design
  • cross-functional collaboration
  • clear communication across technical and non-technical audiences
  • high agency
  • strong product sense
  • bias toward building durable improvements

Nice to have

  • Mandarin
  • Korean
  • Japanese

What the JD emphasized

  • shipping production systems end-to-end is a strong plus
  • building AI applications, agents, or evaluation systems
  • translating their challenges into concrete technical signals
  • cross-functional collaboration

Other signals

  • customer-facing
  • product feedback loop
  • evaluation systems
  • agent prototyping