Lead Technology Product Manager, AI Quality & Evaluation

Wolters Kluwer•Coppell, MA

4d•Hybrid

About The Position

At Wolters Kluwer Health, the UpToDate suite supports millions of clinical decisions every day. As AI becomes part of healthcare workflows, this role helps ensure AI-enabled experiences are evaluated, monitored, and improved continuously so clinicians and care teams can trust the information and interactions they rely on. Working under product leadership and in close partnership with clinical, technical, and data experts, the Senior Product Manager translates clinical quality standards and evaluation strategy into scalable product capabilities. The role operationalizes expert-defined standards through usable tools, repeatable workflows, measurable signals, and evidence that supports product decisions, customer trust, and responsible AI. It does not own the clinical quality standard or statistical methodology. The position drives discovery and delivery of defined AI quality and evaluation capabilities, including tooling, automation, monitoring, evidence capture, reporting, review workflows, issue triage, launch readiness, and post-launch monitoring. It also turns evaluation insights into product improvements and communicates AI quality and evaluation practices to internal and customer-facing stakeholders.

Requirements

5+ years of product management experience in healthcare, enterprise SaaS, data-driven products, platform products, quality, or related areas.
Strong product discovery and execution skills, including requirements definition, roadmap planning, experimentation, and metrics-driven decision-making.
Ability to translate complex clinical, technical, quality, or risk concepts into practical product requirements and workflows.
Experience working with engineering, data, clinical, compliance, customer-facing, or operational stakeholders.
Strong analytical thinking and comfort defining metrics, dashboards, workflows, and decision criteria.
Strong communication skills, especially around quality, trust, tradeoffs, evidence, and customer value.
Curiosity and learning agility around AI, evaluation methods, responsible AI, and emerging technologies.

Nice To Haves

Experience with AI-enabled products, healthcare technology, quality tooling, data products, search/retrieval quality, content quality, clinical validation, or decision-support products.
Familiarity with AI evaluation methods, benchmarks, monitoring, human-in-the-loop review, automation, or applied machine learning concepts.
Experience in healthcare, clinical workflows, regulated environments, or professional-information products.
Experience supporting customer-facing narratives around product quality, trust, or responsible technology.

Responsibilities

Translate expert-defined quality standards and evaluation methods into product requirements, workflows, and roadmap priorities.
Drive discovery and delivery for AI quality and evaluation capabilities, including tooling, automation, monitoring, evidence capture, and reporting.
Partner with clinical, data science, engineering, product, legal, compliance, and customer-facing teams to operationalize AI evaluation before and after launch.
Identify opportunities to automate and scale evaluation workflows while preserving appropriate expert oversight.
Define product requirements for review workflows, issue triage, launch readiness, post-launch monitoring, and quality reporting.
Use evaluation insights to inform product improvements, user experience, content quality, model behavior, and operational processes.
Track emerging market practices and customer expectations related to AI quality, evaluation, benchmarking, and responsible AI.
Translate AI quality and evaluation practices into clear narratives for product leaders, customer-facing teams, and internal stakeholders.