Lead Technical Product Manager – Generative AI

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Role Summary 

Lead Technical Product Manager – Lead Technical Product Manager – Generative AI is an impactful individual contributor who transforms strategic AI initiatives and product vision into executable backlog items the team can deliver. This role bridges product strategy and agile product ownership, development, and execution of the tactical delivery of generative AI capabilities through disciplined backlog management and agile practices across multiple TAA modules. Reporting to the Director of Innovation, you will partner daily with Product Managers, Engineers, and UX to decompose epics into features and INVEST-compliant user stories, ensuring development teams have clear, prioritized work that delivers customer value incrementally. This position requires deep technical understanding of generative AI combined with exceptional agile product ownership skills to drive rapid iteration and continuous customer feedback cycles. You will advise management on release readiness and risk and bring the voice of the customer into the team to ship outcomes that solve real problems. 

About InnovateHub 

InnovateHub operates as Wolters Kluwer's internal innovation accelerator within TAA North America Professional Business Unit, functioning like a startup across the division. We co-design with customers, run lean experiments, and ship high-value capabilities quickly through rapid validation cycles. We partner with product and engineering teams to bring responsible Generative AI into real workflows, grounded in authoritative content and built on the Microsoft Azure ecosystem. Our approach emphasizes customer obsession, build-measure-learn iterations, and fast value delivery to transform how professionals work. 

Essential Duties and Responsibilities 

Backlog Ownership & Agile Execution (30%) 

• Lead the integrated plan for work that spans multiple modules; align product, engineering, and UX to support rapid GTM 

• Transform epics into clear, INVEST features and user stories (Independent, Negotiable, Valuable, Estimable, Small, Testable) with precise acceptance criteria and Definition of Ready/Done 

• Ensure voice of customer and market data flows into sprint planning and backlog prioritization; translate customer feedback into actionable user stories 

• Maintain a prioritized backlog in Azure DevOps Boards with 2-3 sprints of refined, ready work, visible dependencies, and unblocked paths to delivery 

• Apply lightweight prioritization methods (value, risk, effort, sequencing, cost of delay) with documented rationale 

• Lead backlog refinement sessions, sprint planning, and story elaboration with development teams 

• Partner with Engineering on slicing, technical feasibility, release planning, feature flags, and canary rollouts 

• Collaborate with Scrum Master to optimize team flow metrics, maintain predictable delivery, and remove impediments 

• Apply eXtreme Programming (XP) practices where appropriate, including test-driven development support 

Generative AI Product Development (25%) 

• Specify product requirements for Azure OpenAI-based features, including grounding to authoritative sources, citation behavior, refusal/abstain rules, and graceful error handling 

• Understand customer workflows and jobs-to-be-done to effectively decompose AI-driven solutions into implementable features; identify where automation/AI can deliver value within existing user journeys 

• Collaborate on RAG requirements: content sources, chun