Product Manager - AI

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 future investment decisions. Customer and Banker Experience Integration: Ensure AI capabilities are integrated into customer and teammate experiences in ways that feel intuitive and add genuine value, not bolted on as features. Partner with Channel Product owners across Consumer to embed AI into the product experiences they own, creating intelligent moments across the customer lifecycle: personalized guidance, proactive alerts, smarter search, faster service resolution. Advocate for the customer and teammate perspective in every AI design decision, ensuring that AI outputs are trustworthy, useful, and contextually appropriate. Champion consistency across channels, so that AI‑powered experiences in digital banking, the contact center, and advisor tools feel like one bank, not separate systems. Voice AI: Own the end‑to‑end Voice AI product strategy across inbound and outbound use cases, including call containment, payment reminders, servicing, and authentication, with explicit accountability for containment rates, transfer accuracy, and customer satisfaction. Balance cost takeout objectives with customer trust and regulatory exposure, explicitly deciding where Voice AI should fully automate versus where human escalation is required. Ensure Voice AI experiences feel consistent with Valley’s brand voice, disclosures, and service standards across channels (voice, chat, digital). Own the “last mile” experience: how Voice AI hands off to agents, how errors are explained, and how customers regain trust when the AI is wrong. Establish clear Voice AI success metrics beyond containment, including incorrect containment/pre‑containment rate, transfer quality (context passed to human agents), customer recontact rates after AI interactions, and ensure Voice AI ROI reporting separates true deflection from shifted or deferred workload. Responsible AI and Risk: Serve as the Consumer Bank’s internal owner of responsible AI practices, ensuring that models are evaluated for bias, fairness, and explainability before deployment. Partner with Compliance, Risk, and Legal to navigate the regulatory landscape for the Consumer Bank’s AI portfolio, including fair lending implications, model risk management requirements, and emerging AI governance frameworks. Build internal literacy around AI across the Consumer Bank, helping business partners understand what AI can and cannot do, and setting realistic expectations for what initiatives will deliver. Own the prioritization and sequencing of fraud AI initiatives (check fraud, deposit fraud, AML triage), ensuring models deployed where false positives, false negatives, and investigation effort materially impact cost, risk, or customer experience. Explicitly manage tradeoffs between fraud loss reduction and customer friction, ensuring AI reduces risk without degrading legitimate customer activity. Define fraud AI KPIs that capture net fraud loss avoided, investigator effort saved, customer impact from false positives, requiring pre‑launch baselines and post‑launch validation so fraud models are defensible in audits and model risk reviews. Responsibilities Include But Are Not Limited To Own product strategy and roadmap, aligning initiatives to business goals, customer needs, and performance insights. Manage end‑to‑end digital experiences, identifying and prioritizing improvements that enhance usability, conversion, engagement, and efficiency. Define and track key performance metrics (e.g., adoption, conversion, activation, engagement, satisfaction) and use data to inform decisions. Leverage data and AI‑driven insights to identify opportunities for personalization, automation, and improved customer outcomes. Translate business needs into product requirements, including user stories, acceptance criteria, and backlog prioritization. Partner with technology and design teams to deliver high‑quality, scalable solutions in an agile environment. Drive ongoing optimization, including experimentation (A/B testing), iterative improvements, and continuous learning. Collaborate across stakeholders to ensure alignment with business, regulatory, risk, and operational requirements. Act as the voice of the customer, ensuring solutions are intuitive, integrated, and aligned to customer expectations. Evaluate emerging technologies, including AI and automation capabilities, to enhance product functionality and operational efficiency. Monitor product performance post‑launch, identifying issues, risks, and opportunities to improve outcomes. Required Skills Ability to prioritize and manage workflow. Ability to work in a team environment. Ability to build trust, value others, communicate effectively, drive execution, foster innovation, focus on the customer, collaborate with others, solve problems creatively, and demonstrate high integrity. Be an expert with respect to the competition. Demonstrate the ability to interact and cooperate with all company employees. Excellent written and verbal communication skills. Expertise using Microsoft Office applications. Required Experience High School or GED and a minimum of 5 years in product management, product development or product ownership. Demonstrated experience managing end‑to‑end product lifecycle. Preferred Experience Business degree in Business, Design, Technology, or related field. Background in service design, journey mapping, or design systems. Familiarity with AI‑enabled products and responsible AI design principles. Experience working across digital and assisted channels. #J-18808-Ljbffr