Product Manager - AI

At Valley Bank, we believe in people’s growth potential. We invest in it. We protect it. We focus it. For nearly 100 years, we’ve been the Bank that clients from every industry turn to for our expertise, strategies, and advice–building the kind of trust that can fuel every goal. We are the leading relationship bank built for growth–with over $60 billion in assets, 3,800 experts, and more than 200 consumer branches and commercial banking offices in communities across the US.

At Valley, we’re all driven by an ambition that goes deeper than just having a job. That’s why when you work for us, we make it our goal to help you focus on what drives you–working to turn your passions and strengths into assets you can use to propel your ambitions and build the professional legacy you want. Because when we say we’re a relationship bank built for growth, that’s not just reserved for our clients–that includes all our associates as well.

The AI Product Owner is accountable for ensuring that each initiative in Valley’s Consumer Bank AI portfolio is anchored to a clear business problem, delivers measurable value to customers or teammates.

AI initiatives fail most often not because the technology doesn’t work, but because no one owns the product problem with discipline. Engineers build models; vendors pitch capabilities. Without strong product ownership, organizations end up with solutions in search of problems, pilots that never scale, and AI investments that cannot be connected to outcomes. This role closes that gap.

The AI Product Owner will work in close partnership with Valley’s technology team to shape the AI roadmap, define what success looks like for each initiative, and drive adoption across business lines. This role is a connective force across the Consumer Bank organization, ensuring AI capabilities are deployed in ways that create seamless, intelligent experiences for Valley’s customers and teammates.

Key Responsibilities

AI Strategy and Roadmap Ownership

• Own the Consumer Bank AI product roadmap and Portfolio ensuring each initiative is tied to a specific business outcome: cost reduction, revenue growth, customer retention, operational efficiency, or experience improvement.
• Work with business line leaders across Consumer Banking to identify the highest-value problems where AI can deliver a step-change in performance.
• Prioritize AI investments using a rigorous cost-benefit framework, making explicit tradeoffs between complexity, data readiness, regulatory risk, and expected return.
• Translate strategic priorities into a sequenced roadmap that technology teams can execute against, with clear milestones and measurable outcomes at each stage.
• Maintain a forward-looking view of AI capabilities and market developments, identifying where Valley should invest ahead of the curve and where it should wait for the technology to mature.

Technology Partnership and Delivery

• Serve as the product counterpart to Valley’s AI and technology teams, co-owning delivery from problem definition through deployment and optimization.
• Define clear problem statements, success criteria, and evaluation frameworks before any model development or vendor selection begins, ensuring technology investment is preceded by business clarity.
• Participate in model design and evaluation reviews, asking the right product questions: Does this work for our customers or teammates? Can we explain this decision? What happens when it’s wrong?
• Evaluate AI vendors and platform partners, assessing their capabilities against Valley’s specific use cases and holding them accountable to business outcomes, not just technical benefits.
• Drive the transition from pilot to production, owning the organizational, process, and experience changes required to make AI solutions scale beyond proof-of-concept.

Business Outcome Measurement

• Define the KPIs and measurement frameworks for every AI initiative before it launches, establishing baseline metrics and target outcomes that create clear accountability.
• Build reporting that connects AI performance to business results, making the ROI of AI investment visible and defensible to senior leadership.
• Monitor deployed AI solutions continuously, identifying degradation, drift, or unintended consequences and driving rapid response when performance falls short.
• Conduct regular post-implementation reviews to capture learnings, quantify realized value, and inform futu…