Applied AI Product Manager

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An Applied AI Product Manager is a senior individual contributor responsible for ensuring a product’s value and viability within a product line. This role involves leading empowered, cross-functional product teams to solve moderate complexity customer problems that align with high value business needs. The Applied AI Product Manager is accountable for the product’s success, from vision to execution, and collaborates closely with various functions and stakeholders to deliver valuable, viable, usable, and feasible solutions. The Applied AI Product Manager harnesses AI and agentic tools to compress the concept-to-cash learning loop—automating analysis, prototyping, and compliance detail-work so the team can focus on the human judgment AI cannot replace: product sense-making. The Applied AI Product Manager plays a crucial role in ensuring the success of our high value, moderately complex products by balancing customer needs with business objectives. This role requires a blend of strategic vision, analytical skills, and collaborative teamwork to deliver valuable, viable, usable, and feasible solutions. It demands significant experience in the modern product management craft and a drive for continuous improvement—amplified by the fluent, responsible use of AI to learn faster and earn faster. Recruiting for this role ends on 9/30/2026. Work you’ll do Product Accountability Responsible and accountable for the product's value and viability showcasing a measurable Return on Investments (ROI) Drive strategy-aligned solutions to achieve product value objectives. Formulate and achieve Key Performance Indicators (KPIs) for identified problems to solve. Measure KPIs and analyze outcomes to inform future strategies. Leverage AI to harvest outcome evidence early and often, lowering total cost of ownership (TCO). Vision and Strategy Co-create, own, and evangelize the product vision, strategy, and roadmap, using AI to deepen domain knowledge and simulate future scenarios to chart pathways others have not yet seen. Align product objectives with the product line and business goals. Co-create in collaboration with business stakeholders, engineering, experience, and delivery. Use AI to expedite research, gather evidence, bolster domain knowledge, and craft and innovative visions backed by compelling strategic rationale. Market and User Engagement Conduct user research and competitive analysis, using AI agents to synthesize research at speed—accelerating the data crunching, ensuring the human connection. Engage the team with users and stakeholders through continuous research and direct interactions. Collaborate and guide the team toward solutions that address priority user and business needs. Apply analytical skills to analyze data and derive actionable insights, shifting from waiting on analysis to working on insights. Adopt innovative and experimental approaches to solving complex problems, including AI-built, disposable prototypes that validate solutions quickly and retire bad ideas just as fast. Collaboration and Teamwork Work side-by-side with cross-functional (business, engineering, experience, and delivery) team members to achieve KPI outcomes. Promote a product operating model that emphasizes outcomes over output (minimize overproduction while maximizing value). Build empowered teams and product communities who exhibit