Lead Product Manager-(AI

Responsibilities

• 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?

• 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
• 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