AI Product Manager – AI for Operations

Job Description

AI Product Manager, VP | JPMorgan Chase

The Tone:
This is a high-visibility role at JPMorgan Chase, focused on building the next generation of AI and autonomous agents. The company is transforming bank operations by applying the latest advancements in agentic AI and large language models to automate workflows, improve outcomes, and deliver impact at enterprise scale. This position offers meaningful impact and strong growth opportunities for those who enjoy working at the intersection of product, AI, and complex operational systems.

The TL;DR
• Role: Full Time
• Type: Full-time
• Team: AI for Operations team
• Mission: Build the next generation of AI and autonomous agents that can reason, plan, act, and learn to solve critical operations problems at massive scale.
• Tech Stack: large language model architectures, prompting, context engineering, fine-tuning, retrieval-augmented generation, model context protocols, agentic frameworks

What You’ll Actually Do
• Strategy: Identify opportunities where AI can improve key business outcomes and operational performance, translating user and business needs into product strategy, priorities, and actionable requirements.
• Ownership: Own product roadmaps and write Product Requirements Documents (PRDs) for agentic AI pipelines and orchestrations to automate bank operations and workflows.
• Leadership: Lead cross-functional teams of engineers, designers, analysts, and business stakeholders from concept through launch, guiding technical and non-technical decision-making.
• Execution: Drive day-to-day decisions across product, design, and engineering to deliver measurable, reliable, and high-quality outcomes.
• Alignment: Present product direction, progress, and trade-offs to senior leaders across the organization to gain alignment and buy-in.

The Must-Haves
• Background: Bachelor’s degree or equivalent practical experience with demonstrated experience in product management or a related technical role.
• Experience: Demonstrated experience operating in a strong product management culture, with proven ability to own the full product lifecycle, including product documentation and execution through launch, and leading cross-functional teams through technical and non-technical decisions.
• Skills: Working knowledge of large language model architectures and applied methods including prompting, context engineering, fine-tuning, retrieval-augmented generation, model context protocols, and agentic frameworks.
• Bonus: An advanced degree in computer science, engineering, or a related field; experience defining robust evaluation sets and leading quantitative and qualitative evaluation cycles to improve quality and reliability; a track record of delivering and launching successful products at scale; experience leading technology transformation for large digital operations; and experience building products in highly complex, large-scale backend environments.