Develop clear prioritization recommendations that balance customer impact, business value, feasibility, platform readiness, risk, and strategic fit. Build alignment across product, engineering, design, data science, and business stakeholders around AI product priorities and expected outcomes. Serve as a key connector across product domains, AI platform teams, engineering, design, architecture, legal, security, and go-to-market partners for these agentic solutions. Guide AI product capabilities through the full lifecycle, from discovery and opportunity assessment through development, preview, launch, adoption, and iteration. Support rapid experimentation while maintaining focus on customer value, product quality, responsible AI practices, and enterprise readiness. Define and track success metrics such as adoption, task completion, productivity improvement, workflow quality, customer satisfaction, and business impact. Partner with customer-facing teams to gather feedback, validate use cases, and inform future roadmap decisions. Concept-to-Product Orchestration: Partner with AI teams to ensure capabilities are built for "product-readiness," focusing on customer usability, scalability, latency, and real-world utility. Governance Adherence: Act as the guardian of AI integrity for scope, ensuring models and agents adhere to UKG's governance frameworks, "People-First AI" ethics, and global regulatory standards. Required Capabilities: AI Technical Fluency: Ability to engage deeply with technical AI teams on evaluations (e.g., precision/recall, confidence scores) while translating those technicalities into business value. Domain Expertise: Proven track record of shipping production-grade AI/ML products (e.g., skills, agents, recommendation engines, forecasting, or LLM-based functionality). Vertical Knowledge and Portability: Deep understanding of the operational challenges in Healthcare, Retail, other frontline workforce management with success in taking a technical solution from one industry and successfully adapting it for another Entrepreneurial Mindset with Strategic product leadership: Ability to bring structure to ambiguous AI opportunities and translate them into clear product strategy, priorities, and execution plans. Cross-functional influence: Ability to align stakeholders across product, engineering, design, data science, legal, security, and business teams without relying solely on formal authority. Customer workflow orientation: Proven ability to understand complex customer workflows and identify where technology can reduce friction, improve outcomes, or increase productivity. Platform thinking: Ability to balance customer-facing product needs with reusable platform capabilities, scalability, and long-term architectural fit. Enterprise SaaS execution: Experience delivering complex SaaS products from concept through launch, adoption, and iteration. Translate early AI concepts into clear, actionable product requirements that define user needs, workflow context, expected outcomes, success metrics, and guardrail requirements. Partner closely with platform and engineering teams to ensure AI-powered experiences are scalable, secure, reliable, and aligned with broader product architecture. Help define reusable patterns for how agents, assistants, and intelligent workflows are designed, evaluated, launched, and improved over time. Ensure product requirements account for data needs, integration points, permissions, user controls, transparency, and operational readiness. Collaborate with UX and research teams to create AI experiences that feel intuitive, useful, and trustworthy for customers. 10+ years of experience in product management, with a significant focus on delivering complex SaaS products. 5+ years of experience in AI/ML Product Management, specifically partnering with Data Science teams to ship production-grade models or agents. Data-Driven Mindset: Strong analytical skills to evaluate business processes and identify high-impact opportunities for automation and predictive intelligence. Expert Communication: Exceptional at writing functional specifications for AI systems and confidently engaging with executives and customers to present platform updates. Healthcare/WFM Context: Prior experience in Healthcare Workforce Management or Clinical Staffing is a major plus. The ideal candidate is a seasoned product leader who thrives in ambiguity, brings structure to emerging technology opportunities, and knows how to focus teams on the highest-value problems. They are comfortable moving between customer workflow discussions, technical platform conversations, product requirement reviews, and executive-level prioritization decisions. They are not responsible for building models themselves, but they are technically credible, product-minded, and able to translate AI potential into practical, trusted, enterprise-grade product experiences.
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