Principal Product Manager - Technical, External Services, Artificial General Intelligence (agi): AI Services

Amazon Amazon · Big Tech · Santa Barbara, CA · Project/Program/Product Management--Technical

Principal Product Manager, Technical (PMT-ES) for Amazon's Artificial General Intelligence (AGI) organization, focusing on strategy and delivery of externally-launched AI services. This role involves defining, scaling, and managing customer-facing AI services that bring state-of-the-art models to AWS customers, encompassing the full product lifecycle from concept to growth, including pricing, P&L, and business metrics.

What you'd actually do

  1. Own product strategy, roadmap, and business outcomes for customer-facing AI service(s) within the AGI organization
  2. Work backwards from customer needs to define how SOTA AI capabilities become generally-available AWS services
  3. Drive the full product lifecycle from concept through public launch through growth — including pricing, packaging, and adoption strategy
  4. Partner with science and engineering teams to make the right capability and timeline tradeoffs
  5. Engage directly with customers and field teams to shape the roadmap and validate product-market fit

Skills

Required

  • 7+ years of working as a Technical Product Manager experience
  • 5+ years of technical (software development, network development, IT, other related) experience
  • Experience delivering large-scale SaaS, PaaS or LaaS products where you are responsible for the full product lifecycle, from concept through GTM (go to market)

Nice to have

  • Experience developing, deploying and managing AI products at scale
  • Experience with training and deploying machine learning systems to solve large-scale optimizations, or experience dealing effectively with customers during problem resolution and operating efficiently under pressure
  • Experience communicating complex business concepts in verbal and written form
  • Knowledge of AWS services, market segments, customer base and industry verticals
  • Track record of launching and scaling 0-to-1 products in ambiguous, fast-moving domains
  • Experience working directly with applied science and research teams — translating customer requirements into model capabilities and translating model advances into product features

What the JD emphasized

  • launching and scaling 0-to-1 products
  • developing, deploying and managing AI products at scale
  • training and deploying machine learning systems

Other signals

  • launching and scaling 0-to-1 products
  • customer-facing AI services
  • turning research into production AWS services