Sr. Tpm, Genai, Catalog Systems

Amazon Amazon · Big Tech · NY +1 · Project/Program/Product Management--Technical

The Sr. TPM will own the technical execution and strategy for product data enrichment using Generative AI, foundation models, and multimodal LLMs. This role involves translating business requirements into technical specifications, coordinating development across multiple engineering teams, and ensuring seamless integration into AI training pipelines. The goal is to bring GenAI enrichment capabilities to production at global scale for Amazon's next-generation product data systems.

What you'd actually do

  1. Convert business requirements into detailed technical specifications, defining performance standards and system architectures that enable parallel team execution.
  2. Develop enrichment strategies that determine optimal model selection for specific tasks to maximize ROI and quality.
  3. Create and track project milestones across teams while serving as the primary technical contact to resolve ambiguities and remove blockers.
  4. Identify system changes needed, estimate effort with development managers, and create multi-team implementation timelines.
  5. Establish visibility mechanisms that provide stakeholders clear insight into enrichment pipeline status, performance, and delivery timelines.

Skills

Required

  • 7+ years of working directly with engineering teams experience
  • 5+ years of technical product or program management experience
  • 3+ years of software development experience
  • 5+ years of technical program management working directly with software engineering teams experience
  • Experience managing programs across cross functional teams, building processes and coordinating release schedules

Nice to have

  • 5+ years of project management disciplines including scope, schedule, budget, quality, along with risk and critical path management experience
  • Experience managing projects across cross functional teams, building sustainable processes and coordinating release schedules
  • Experience defining KPI's/SLA's used to drive multi-million dollar businesses and reporting to senior leadership
  • Experience developing, deploying and managing AI products at scale

What the JD emphasized

  • GenAI-powered enrichment capabilities
  • AI training pipelines
  • foundation models
  • multimodal LLMs
  • autonomous evaluation systems

Other signals

  • GenAI-powered enrichment capabilities
  • foundation models, multimodal LLMs
  • autonomous evaluation systems
  • AI training pipelines