Principal Product Manager, Data Intelligence and AI Governance

Adobe
U.S. / California2026-06-23Full time

About the job

Embrace the role of a Principal Product Manager, Data Intelligence & AI Governance and lead the strategic direction of metadata, governance, and AI readiness across Adobe’s enterprise data platform. Drive cross-functional alignment, shape unified operator experiences, and ensure data quality and agent-readiness for enterprise AI solutions. Make a lasting impact at the forefront of data innovation.

Responsibilities

Define and drive Adobe's enterprise metadata model and own the product roadmap for metadata enrichment, normalization, and publication.

Own the product definition of 'agent-ready data' and develop the agent readiness scoring model and HITL governance framework.

Drive the product strategy for a unified operator console that spans across multiple systems, replacing separate registry UIs.

Define cross-layer views for operators, including dependency graphs, freshness dashboards, and agent readiness panels.

Qualifications

Minimum

10+ years of product management experience, with at least 3 years in data platform, data infrastructure, or enterprise data products.

Bachelor's degree in Computer Science, Engineering, or a related field.

Demonstrated experience owning a data governance, metadata, or data quality product.

Deep familiarity with the AI/ML data lifecycle and what makes data 'agent-ready'.

Ability to write engineering PRDs and design quick prototypes through vibe-coding.

Track record of driving cross-functional alignment across engineering, data science, and platform teams.

Strong systems thinking to reason about a data platform as a causal chain.

Preferred

Experience with event streaming, schema registries, or data pipeline governance (e.g. Kafka, Databricks, Unity Catalog).

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 in production data systems.

Experience building or operating a unified data catalog (e.g., Open Metadata, Amundsen, DataHub, Atlan).

Background in a platform PM role with multiple upstream/downstream product dependencies.