Senior Product Manager, Data Platform Knowledge & Retrieval
Overview
You will own the knowledge tier of Adobe's data intelligence stack, turning curated definitions into retrieval-ready, agent-optimized knowledge assets consumed daily by AI agents and enterprise systems. You'll drive a 6-12 month roadmap for knowledge-asset modeling, retrieval APIs, and embedding/RAG pipelines, working shoulder-to-shoulder with engineering and data science. This role sits at the sharp end of Adobe's agent-ready data strategy, where you'll balance roadmap ambiguity with specification precision. You'll build human-in-the-loop correction workflows and trust signals like freshness and lineage, all while prototyping with Claude Code to de-risk build decisions. What makes this different: you own the full lifecycle of knowledge assets, from ingestion to deprecation, and your work directly shapes how Adobe's agents retrieve trustworthy information.
What You'll Do8
- 1Own the 6-12 month roadmap for knowledge-asset modeling, retrieval APIs, and agent-integration interfaces, prioritizing against shifting platform needs.
- 2Lead delivery from inception to launch, making quality, customer-value, and time-to-market tradeoffs while mitigating risk across engineering and build.
- 3Define how curated definitions are ingested, versioned, and deprecated, ensuring consuming agents never retrieve stale or orphaned knowledge.
- 4Deliver trust signals for the knowledge layer, including freshness, lineage, and quality, contributing to the platform-wide agent readiness score.
- 5Build human-in-the-loop correction workflows, defining triggers for human review and how corrections propagate to downstream consumers.
- 6Write engineering PRDs that translate platform requirements into prioritized features, crisp specifications, and concrete performance measures.
- 7Partner with peer PMs owning metadata, event telemetry, and cross-cutting governance to build retrieval and embedding surfaces on governed foundations.
- 8Prototype with Claude Code to stand up quick, testable prototypes that reduce build risk before engineering dedication.
Requirements7
- 17+ years of product management experience, including 2+ years owning a data platform or enterprise data product end to end.
- 2Working knowledge of knowledge-graph concepts, embedding pipelines, RAG architectures, MCP servers, and agent skills.
- 3Experience with human-in-the-loop quality and correction workflows in production data systems.
- 4Ability to write engineering PRDs that translate complex technical systems into user problems, prioritized features, and measurable metrics.
- 5Ability to build quick prototypes via vibe-coding with Claude Code to de-risk decisions.
- 6Systems thinking to reason about the platform as a causal chain and articulate how decisions drive adoption and retention.
- 7Proven cross-functional influence across engineering and program, operating at both ambiguous and precise altitudes.
Salary Insight
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