Principal Product Manager, Data Intelligence and AI Governance

Adobe Adobe · Enterprise · San Jose, CA

Principal Product Manager for Data Intelligence and AI Governance at Adobe, focusing on the data platform's trustworthiness and agent readiness. This role owns the strategic direction for metadata, governance frameworks, data lineage, and ensuring enterprise data assets are ready for AI consumption. It's a platform-level position responsible for the quality, coherence, and trustworthiness of data throughout the platform, and for the unified operator experience.

What you'd actually do

  1. Define and drive Adobe's enterprise metadata model — what gets catalogued, how it is structured, what it means, and how it stays current across systems.
  2. Own the product roadmap for metadata enrichment, normalization, and publication — including benchmark definitions, event schemas, data job lineage, and entity relationships.
  3. Own the product definition of 'agent-ready data' — the governance, freshness, lineage, and trust properties
  4. Develop and drive the agent readiness scoring model: a composite, per-agent health score that spans signal quality, metadata integrity, and knowledge freshness.
  5. Drive the product strategy for a unified operator console that spans across multiple systems— replacing separate registry UIs with a single, coherent governance and observability surface.

Skills

Required

  • 10+ years of product management experience
  • at least 3 years in data platform, data infrastructure, or enterprise data products
  • Demonstrated experience owning a data governance, metadata, or data quality product
  • Deep familiarity with the AI/ML data lifecycle
  • Ability to write engineering PRDs
  • Ability to design quick prototypes
  • Track record of driving cross-functional alignment
  • Strong systems thinking

Nice to have

  • Experience with event streaming, schema registries, or data pipeline governance
  • Familiarity with knowledge graph concepts, embedding pipelines, or retrieval-augmented generation (RAG) architectures, MCP server, Skills
  • Prior exposure to HITL (human-in-the-loop) quality and correction workflows
  • Experience building or operating a unified data catalog
  • Background in a platform PM role

What the JD emphasized

  • AI agent readiness
  • agent-ready data
  • agent readiness scoring model
  • data governance
  • metadata strategy
  • data lineage
  • trustworthy AI data

Other signals

  • AI agent readiness
  • data governance for AI
  • metadata strategy
  • data lineage
  • trustworthy AI data