Senior Manager - AI Product Management

This job posting is anticipated to remain open for 30 days, from 22-Oct-2026. The posting may close early due to the volume of applicants.

Join a financial services firm where your contributions are valued. Edward Jones is a Fortune 500¹ company where people come first. With over 9 million clients and 20,000 financial advisors across the U.S. and Canada, we’re proud to be privately-owned, placing the focus on our clients rather than shareholder returns.

Behind everything we do is our purpose: We partner for positive impact to improve the lives of our clients and colleagues, and together, better our communities and society. We are an innovative, flexible, and inclusive organization that attracts, develops, and inspires performance excellence and a sense of belonging.

People are at the center of our partnership. Edward Jones associates are seen, heard, respected, and supported. This is what we believe makes us the best place to start or build your career.

View our Purpose, Inclusion and Citizenship Report.

¹Fortune 500, published June 2024, data as of December 2023. Compensation provided for using, not obtaining, the rating.

The Senior Manager, AI Product Manager leads a team responsible for a portfolio of AI products and reusable AI capabilities, including AI models, agents, retrieval systems, knowledge assets, platform capabilities, and other emerging AI technologies. This role combines the strategic product scope and expertise expected of a Lead AI Product Manager with direct accountability for associate leadership, team performance, and capability development.

The Senior Manager treats AI itself as the product —owning product strategy, discovery, prioritization, adoption, lifecycle management, and measurable outcomes for reusable AI capabilities that serve multiple business areas, products, customer experiences, and enterprise workflows. The role ensures that AI capabilities are designed as durable, scalable products rather than one-time solutions.

Operating with significant autonomy, the Senior Manager shapes product direction, translates enterprise priorities and customer needs into roadmaps and investment decisions, and ensures measurable value creation. The role balances hands-on product leadership with responsibility for leading, coaching, and developing AI Product Managers and establishing clear priorities, accountability, and effective ways of working across the team.

The Senior Manager partners closely with leaders and colleagues across EJ Labs, Engineering, Data, Product Management, Architecture, Experience, Risk, and Business and Functional areas. The role influences enterprise AI direction, aligns interconnected products and capabilities, and ensures AI products remain reusable, explainable, reliable, well-governed, and aligned with responsible AI practices.

What You’ll Do

• Lead a team of AI Product Managers responsible for a portfolio of strategic AI products and reusable enterprise capabilities.
• Define product strategy, value propositions, outcomes, priorities, roadmaps, investment needs, and success measures for assigned AI product and capability domains, balancing customer value, enterprise benefit, cost, risk, feasibility, and time to value.
• Translate enterprise priorities, customer needs, market signals, and technical insights into scalable product strategies, requirements, evaluation criteria, and prioritized work.
• Establish and lead rigorous continuous discovery practices across the portfolio, ensuring teams build deep understanding of customer needs, workflows, pain points, and desired outcomes and use primary customer research, prototypes, experiments, evaluations, proofs of concept, and pilots to test assumptions and guide product decisions.
• Use customer evidence, product analytics, technical findings, and business measures to guide prioritization, investment, scaling, optimization, and retirement decisions.
• Own the full product lifecycle from discovery and launch through adoption, operation, modernization, and retirement, including integration, enablement, documentation, change, support, and monitoring strategies.
• Apply systems and platform thinking to ensure reusable AI products have clear customers, use cases, boundaries, interfaces, dependencies, supported uses, limitations, ownership, controls, and operating expectations—and operate coherently within the broader enterprise AI ecosystem.
• Establish po…