Principal Product Manager, AI Evaluation and Data Policy

ZoomInfo's Core Data team builds the person and company data that powers our Go-To-Market Intelligence Platform, and we're rebuilding how that data gets made. We're moving from deterministic selection rules to an inference-default model where agents read the evidence and propose answers, and where evaluation — not hand-built logic — decides what ships. We're hiring a Principal Product Manager to own Person Data outcomes end to end and to build the AI evaluation discipline the whole team will run on.

What You'll Do

• Own Person Data end to end, setting the strategy, roadmap, and monthly priorities for contact accuracy, coverage, freshness, and compliance, from cleaning up bogus executive contacts to leadership extraction and person location
• Build and run the AI evaluation engine: define what "correct" means per attribute, curate golden sets with the research team, stand up LLM-as-judge gates, and set confidence thresholds for auto-accept, auto-reject, and human adjudication
• Lead the pivot from rules to agents by writing the policy clauses agents follow, proving each step in shadow mode against the gold set, and retiring legacy selection logic once the data supports it
• Decide where AI earns its place in the pipeline and where classical tooling wins, reasoning explicitly about cost per row, latency, determinism, and auditability
• Tackle entity resolution as the hard core of the problem, bringing a clear model for canonical identity, match confidence, and the cost asymmetry between false merges and missed matches
• Own the privacy roadmap for person data, including suppression, opt-out, and notification, in partnership with Legal and Privacy
• Prototype adjudication agents and evaluations in code alongside the AI engineer and data science team, committing directly to the shared repository
• Act as the hub across Person Data engineering, Match, Research, Data Science, Web Data acquisition, and Privacy, and represent the roadmap clearly to product and data leadership

What You Bring

Must-Have

• 8+ years of product management experience, with meaningful time owning data products or data platforms at scale
• Hands-on experience with data pipelines and a working understanding of how records move from ingestion through processing to a served dataset
• Direct experience with entity resolution, record linkage, or matching systems, including canonical IDs, match confidence, survivorship rules, and precision/recall trade-offs
• Demonstrated, current use of AI to improve data systems in production, with the ability to describe how you kept accuracy from degrading
• Experience designing evaluations for model output, including golden sets, precision and recall, LLM-as-judge, human-in-the-loop routing, and production drift monitoring

Preferred

• Experience with incremental or streaming data pipelines, rather than batch rebuilds
• Experience with contact, person, or identity data, or with B2B company data
• Familiarity with privacy regulation as it applies to published personal data (GDPR, CCPA, DNC, and international notification regimes)
• Experience with Claude or comparable frontier models, agent frameworks, and eval harnesses

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