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Principal AI Product Engineer

Skills
Computer ScienceAdoptionComplex SystemsContextDefaultsFoundationsReadiness
Role

What the job involves

The main requirements, responsibilities and hiring steps.

Requirements

  • 8+ years of engineering experience with end-to-end ownership of large business-critical systems
  • Deep intuition for why models fail from experience predating the LLM boom
  • Experience with classical NLP or ML to support sound architectural decisions
  • Experience formulating architectural strategy at the organization level
  • Track record of mentoring senior and staff engineers
  • Proven ability to ship AI-powered products to production
  • Experience with evaluation monitoring and safety for AI systems
  • Ability to work independently with minimal guidance
  • Strong judgment on build versus buy decisions
  • Experience designing systems across multiple teams

Nice to have

  • product-minded
  • AI-native
  • relentlessly driven
  • decisive
  • hands-on
  • security-minded
  • mission-aligned

Day to day

  • Own outcomes end-to-end by turning high-leverage AI opportunities into shipped capabilities with clear measurement and iteration loops.
  • Define AI technical direction by translating customer problems into practical strategy reference architectures and a roadmap that multiple teams can execute.
  • Lead by implementation through rapid prototyping and reference implementations that prove feasibility de-risk decisions and raise team ambition.
  • Help build shared foundations such as evaluation harnesses retrieval patterns safety guardrails observability and developer experience so teams can ship reliable AI repeatedly.
  • Raise the bar across the organization by mentoring senior and staff engineers leading design reviews and aligning stakeholders to drive adoption.