Lead AI Product Manager for Enterprise AI Solutions

Edward Jones; Washington (District of Columbia); On-site; USD 180,000 - 280,000; Full time

Benefits offered by this job

Bonus program

Job summary

Edward Jones is seeking a Lead AI Product Manager to shape and lead enterprise AI products that serve multiple domains. You will own AI product strategy, discovery, prioritization, adoption, and lifecycle management with measurable value outcomes.

The role demands cross-functional leadership across engineering, data, and risk, driving scalable, reusable AI solutions aligned with responsible AI practices.

Qualifications

• 7+ years of Product Management experience across complex tech or AI products.
• Deep knowledge of enterprise AI technologies, data, and governance.
• Strong ability to translate customer needs into product outcomes and requirements.
• Experience influencing senior leaders and coaching others.

Responsibilities

• Define vision, value proposition, priorities, roadmap, and investment strategy for strategic AI products.
• Lead discovery, tests, and pilots to validate hypotheses and guide investments.
• Own end-to-end lifecycle from discovery to retirement, ensuring customer value and reuse.
• Define end-to-end AI experiences, data needs, and governance considerations.
• Promote interoperable patterns across models, agents, and tools while balancing enterprise scale.
• Serve as trusted advisor to product teams, architecture, security, and risk leaders.

Skills

Product management

AI product strategy

Cross-functional leadership

Discovery & experimentation

Communication to senior leaders

Education

Bachelor's degree

Master's degree (preferred)

Tools

Copilot Studio

Power Platform

Azure AI

Databricks

Job description

Edward Jones is seeking a Lead AI Product Manager to shape and lead enterprise AI products that serve multiple domains. You will own AI product strategy, discovery, prioritization, adoption, and lifecycle management with measurable value outcomes.

The role demands cross-functional leadership across engineering, data, and risk, driving scalable, reusable AI solutions aligned with responsible AI practices.