Lead Product Manager

Partner with product leadership to develop and execute a product strategy where AI is the core value driver, not a feature layer on top of an existing product Build rapid AI prototypes using tools like Cursor, Claude, Replit, or v0 to validate product direction and compress the time from insight to validated concept Define what "good" looks like for AI-powered scheduling outputs: model behavior, success criteria, edge cases, and the trust signals that matter to end users Partner with engineering on prompt design, model tradeoffs, and evaluation pipelines. Contributing technical judgment alongside product direction Work closely with engineering to deliver high-quality AI-powered solutions that exceed customer expectations in healthcare scheduling Build and maintain strong relationships with customers and partners to understand scheduling pain points and translate them into AI product opportunities Partner with cross-functional teams to bring new AI-powered capabilities to market and enable Go-To-Market teams to tell a compelling story about what we've built Define and track AI-specific KPIs, not just adoption metrics, but output quality, scheduling accuracy, time-to-value, and user trust over time Conduct competitive intelligence with an AI lens: what are AI-native scheduling competitors building, where are they winning, and where can UKG's data advantage be decisive? Foster a product culture where hypotheses are tested with working prototypes before engineering investment, not after 7+ years delivering or managing SaaS applications within an Agile environment, including demonstrated experience building or shipping AI-powered products Hands-on experience with AI in your product workflow: prototyping, defining model behavior, and measuring AI output quality, not just managing teams that do it Experience working with tools like Cursor, Replit, v0, Claude, or equivalent to prototype product ideas before handoff to engineering Technical fluency with AI systems: you understand prompt engineering, model tradeoffs, and evaluation basics at a reasoning level. You don't need to code it, but you need to think clearly about it Proven ability to evaluate where AI creates genuine product value versus where it's hype, and to make product bets based on that judgment Exceptional communicator and storyteller: can explain a model limitation to an engineer, frame an AI scheduling capability as a patient-care outcome to a hospital VP, and present a roadmap to a product VP. Adjusting depth and framing for each audience Proven ability to lead through influence and operate across teams without formal authority Deep experience in Workforce Management, Healthcare, or scheduling: either as a domain expert, product professional, or end user who has experienced the problems firsthand Healthcare scheduling expertise with knowledge of acuity matching, certification requirements, compliance constraints, and union rules Familiarity with agentic AI architectures, LLM APIs, or AI/ML product design patterns Experience defining evaluation frameworks or success criteria for probabilistic AI systems