Lead Technology Product Manager, AI Clinical Decision Support

Wolters Kluwer•Chicago, IL

2d•Onsite

About The Position

Build trusted AI experiences that help clinicians get from question to answer faster. At Wolters Kluwer Health, the UpToDate suite supports millions of clinical decisions every day. As AI changes how clinicians search for, interpret, and apply clinical knowledge, we are building product experiences that make trusted guidance easier to access, understand, and use. As Senior Product Manager, AI Clinical Decision Support, you will play a core role in developing AI-enabled experiences for UpToDate's core clinical decision support products. Working under product leadership, you will own discovery and delivery for defined capabilities that improve how users ask clinical questions, navigate evidence-based content, and engage with trusted answers. This role focuses on building useful, responsible, and engaging AI product experiences that support clinical judgment and strengthen the core UpToDate experience.

Requirements

5+ years of product management experience in healthcare, enterprise SaaS, content products, search, workflow, or data-driven products.
Strong product discovery and execution skills, including customer research, experimentation, roadmap development, and metrics-driven decision-making.
Experience translating complex customer problems into intuitive product experiences, clear requirements, and measurable outcomes.
Ability to partner closely with engineering, design, clinical, content, analytics, commercial, and customer-facing teams.
Strong communication, analytical thinking, stakeholder-management, and influencing skills.
Curiosity and learning agility around AI, automation, emerging technologies, and responsible product development.
Ability to operate in ambiguity and make sound product decisions in complex, regulated healthcare environments.

Nice To Haves

Experience with AI-enabled, data-driven, search, content, knowledge, or decision-support products.
Practical understanding of generative AI, retrieval-based systems, recommendation systems, workflow automation, or applied machine learning concepts.
Experience with clinical decision support, healthcare content, point-of-care tools, or professional-information products.
Familiarity with human-in-the-loop workflows, responsible AI practices, model evaluation, or trust and safety considerations.

Responsibilities

Drive discovery and delivery for defined AI-enabled clinical decision support capabilities.
Translate clinician, customer, and business needs into product requirements, experiments, roadmap priorities, and measurable outcomes.
Shape experiences that help clinicians ask questions, find relevant information, understand clinical context, and move from question to action with confidence.
Partner with engineering, design, clinical, content, analytics, customer-facing, and commercial teams from discovery through launch and iteration.
Define success metrics tied to adoption, engagement, trust, user satisfaction, workflow impact, and business value.
Use customer conversations, concept tests, analytics, and feedback to validate user needs and product direction.
Make product decisions that balance customer value, usability, clinical trust, technical feasibility, speed, cost, and responsible AI considerations.
Communicate roadmap priorities, rationale, risks, and tradeoffs clearly across teams and leadership.