Enterprise AI Agents Platform Product Manager

JPMorganChase

Seattle (WA)

On-site

USD 170,000 - 210,000

Full time

2 days ago

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Job summary

JPMorganChase is seeking a Technical Product Manager to lead the AI Agents Platform, shaping the developer experience and governance that engineers rely on across the firm. You will define the product strategy for the agent platform and ensure scalable, safe operations for enterprise AI agents.

Own the ADLC lifecycle and backlog across ADLC, Agent Cloud, Managed Agents, Control Tower, Gateway, and identity.

Qualifications

5+ years in AI product management or a related field.
Advanced knowledge of the Agent development life cycle and Spec Driven Development, design, and data analytics.
Proven ability to lead product life cycle activities including discovery, ideation, strategic development, requirements definition, and value management.
Hands-on experience with LLMs and AI-powered tools to drive productivity.
Strong stakeholder management, communication, and ability to influence cross-functional teams.

Responsibilities

Develop a product strategy and vision for the agent platform and governance services.
Own, maintain, and develop a product backlog across ADLC, Agent Cloud, Managed Agents, the Control Tower, Gateway, Identity, and governance.
Own the Agent Control Tower as the firmwide control plane with canonical identity, lifecycle state, policy status, and operational controls.
Deliver identity and delegation capabilities including multi-hop OBO and short-lived scoped credentials.
Own governance as a service, including the Agent Manifest and release graph, and the System of Record.
Document the ADLC consistently across the SDK and other surfaces, and simplify Managed Agent onboarding during feasibility.
Embed controls for model usage, tool invocation, data access, entitlements, logging, auditability, and human oversight.
Build the framework and track metrics like production conversion, governance automation rate, reliability, and control effectiveness.
Own end-to-end delivery and execution, planning and prioritizing the backlog of supporting scrum teams.
Partner with Legal, Compliance, Risk, Cybersecurity, Model Risk, and Data Governance to operationalize responsible AI as product capabilities.