AI Product Manager

Job Description

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.

• Ensure a data‑driven approach to prioritize the highest‑value AI capabilities, platform enhancements, and user needs.
• Drive adoption, usability, and operational effectiveness of AI products and platforms through continuous measurement and optimization.
• Advocate for reusable AI capabilities, patterns, and platform services that enable enterprise scale, speed to market, and consistent governance.
• Leverage market trends, emerging AI capabilities, user feedback, and business priorities to define and evolve AI product strategy.
• Define product vision, success metrics, and roadmaps for AI platforms, tools, and capabilities.
• Align AI product priorities across Technology, Data, Risk, Security, and business stakeholders to establish an integrated delivery roadmap.
• Regularly reevaluate priorities to optimize capacity against business value, user outcomes, risk considerations, and platform health.
• Leverage OKRs (Objectives and Key Results) and product metrics to guide roadmap decisions and investment priorities.
• Drive the integration of AI platforms and capabilities into business workflows and experiences to maximize adoption and value realization.
• Promote platform modernization, observability, monitoring, governance, and operational excellence practices that improve reliability, transparency, and performance.
• Drive product delivery through the agile lifecycle, from discovery and experimentation through implementation and continuous improvement.
• Leverage product discovery techniques to validate customer needs, identify opportunities, and prioritize the most impactful solutions.
• Partner with cross‑functional teams to establish product‑market fit through research, journey mapping, prototyping, product chartering, and stakeholder engagement.
• Define north‑star and supporting metrics that connect platform performance, user adoption, and business outcomes.
• Continuously measure results against targets and identify opportunities to improve adoption, operational effectiveness, and value delivery.
• Use product metrics, platform telemetry, and user feedback to optimize execution and ensure teams remain focused on the highest‑value work.

• Digital Product Management experience

• Experience managing technology, platform, data, AI, or digital products through the product lifecycle.
• Strong understanding of AI, machine learning, generative AI, or emerging technology concepts and their business applications.
• Ability to balance user needs, business value, technical feasibility, risk considerations, and operational requirements.
• Experience defining and measuring product success through KPIs, OKRs, adoption metrics, operational metrics, and business outcomes.
• Knowledge of software development, platform architecture, APIs, integrations, and agile delivery methodologies.
• Familiarity with AI platform capabilities such as model management, orchestration, monitoring, evaluation, governance, guardrails, and observability.
• Knowledge of risk management, governance, compliance, and controls in a regulated environment.
• Strong analytical, communication, stakeholder management, and problem‑solving skills.
• Ability to translate complex technical concepts into clear business outcomes and product decisions.

• AI product strategy, vision, and planning
• AI products, platforms, and services
• Product discovery and experimentation
• Agile product development
• Adoption and change management
• Performance measurement and optimization
• AI governance and responsible AI
• Platform operations and observability
• Customer and stakeholder research
• Analytics and data‑informed decision…