Senior AI Product Manager

At U.S. Bank, we’re on a journey to do our best. Helping the customers and businesses we serve to make better and smarter financial decisions and enabling the communities we support to grow and succeed. We believe it takes all of us to bring our shared ambition to life, and each person is unique in their potential. A career with U.S. Bank gives you a wide, ever-growing range of opportunities to discover what makes you thrive at every stage of your career.

Try new things, learn new skills and discover what you excel at—all from Day One.

At U.S. Bank, the Digital team is responsible for setting and executing our enterprise-wide digital strategy. We drive incremental growth, increased engagement, loyalty, and retention by delivering excellent experiences. We digitize and automate banking wherever possible, enabling customers to complete tasks on their own when they wish, and pair that with physical branches for when they want help. The Digital team works to empower our customers to make decisions with data and advanced analytics, so they can bank when, where, and how they want, with insights that help them manage their money.

Senior AI Product Manager (Archetype Lead):
The Senior AI Product Manager will lead one of the bank’s core AI archetypes, owning a portfolio of AI use cases from discovery through production and value realization. This role is accountable for defining the AI product strategy, driving delivery in a highly regulated environment, partnering closely with Technology and Risk, and aggressively identifying reuse opportunities to scale trusted AI capabilities across the enterprise.

• 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.
• Serve as a product leader who can navigate and explain tradeoffs between innovation, risk, and time‑to‑value.

• 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.