Senior AI Product Manager

Responsibilities Enable business line value creation by explicitly connecting AI product objectives, key results, and roadmaps to business outcomes including cost savings, revenue growth, productivity gains, and risk reduction. Balance near‑term delivery with longer‑term platform and capability investments to maximize return on AI investments. Leverage business priorities, customer problems, and enterprise AI strategy to define a clear vision for the AI archetype. Define multi‑year AI product strategy including target use cases, users, value hypotheses, technical capabilities, and build vs. buy decisions. Align AI product vision across Technology, Risk, Data, and Business partners to establish an integrated, executable roadmap. Continuously re‑evaluate priorities to optimize capacity against business value, delivery risk, and reuse potential. Integrate AI products and platforms into existing digital and operational experiences to drive measurable business value. Advocate for reusable AI capabilities (patterns, components, guardrails, evaluation approaches) to enable scale, speed to market, and consistent risk posture. Evaluate vendor and platform options for AI capabilities, making informed recommendations on build vs. buy. Drive AI product development through the agile lifecycle, from discovery to pilot to production. Actively engage the quad (Product, Design, Agile, Engineering) to execute strategy and continuously improve delivery effectiveness. Ensure iterative development with clear MVP definitions, success metrics, and learning loops. Partner closely with technical teams to shape solution architecture with an emphasis on reuse, reliability, performance, and operational readiness. Partner with Risk, Compliance, and Governance teams to ensure AI solutions are compliant‑by‑design and meet all enterprise risk requirements. Incorporate risk, control, and approval processes into delivery plans without sacrificing speed or clarity of ownership. Validate AI solutions through adoption, usage, and value realization metrics. Identify drop‑offs, risks, and optimization opportunities post‑launch; drive continuous improvement to increase adoption and sustained impact. Partner with cross‑functional teams to establish product‑market fit using research, discovery workshops, product charters, and journey mapping. Collaborate with communications, training, operations, and business partners to support successful rollout and adoption of AI capabilities. Requirements Senior individual contributor with experience leading medium‑to‑high complexity digital, platform, data, or AI products. Strong technical fluency and comfort working closely with engineering and data science teams. Experience operating in regulated environments with risk, compliance, or control requirements. Demonstrated ability to size opportunities, prioritize investments, and deliver measurable business outcomes. Typically 7–10+ years of product management or closely related experience. #J-18808-Ljbffr