Agent Core Product Manager for Agent Builder

JPMorganChase is seeking a Technical Product Manager to lead the Agent Core product area on the AI Agents Platform. This role will own the Agent SDK and the Model Context Protocol (MCP) SDK, building a developer platform that helps teams design, build, test, register, deploy, monitor, and operate AI agents with governance at enterprise scale.

Role Focus

Own the product strategy and execution for the developer platform underpinning governed AI agent delivery. Establish the Agent SDK and MCP SDK as the preferred, sanctioned path for production agent workflows while enabling safe adoption across the engineering community.

Responsibilities

• Develop and execute product strategy and vision for the Agent SDK and MCP SDK, delivering value to the firm’s builder community and reinforcing the sanctioned SDK pathway for governed production agents.
• Own, maintain, and evolve the product backlog for the SDK line, supporting the roadmap and value proposition across Java, Python, and Go.
• Drive an end-to-end developer experience that reduces time to first governed agent using starter kits, scaffolding, spec driven development workflows, documentation, and trace and error quality, along with self-service tooling.
• Own the MCP SDK roadmap, including a low-code publishing path and a template library enabling partner teams to self-serve and publish their own MCP servers.
• Advance standards-based interoperability with external agent frameworks and development environments using open protocols such as MCP and agent-to-agent (A2A). Deliver migration enablement tooling to bring agents built elsewhere onto the SDK.
• Partner with Forward Deployed Engineering and customer teams to capture the voice of the customer and translate it into prioritized SDK requirements.
• Define and track key product success metrics, including adoption, language parity traction, reliability, developer satisfaction, and registration-to-deployment conversion.
• Own end-to-end delivery and execution, planning and prioritizing the backlog of supporting scrum teams.
• Shape product strategy and vision through thought leadership by influencing stakeholders across Technology, Risk, Compliance, and the business, and promoting SDK adoption.

Requirements

• 5+ years of experience or equivalent expertise in AI product management or a relevant domain area.
• Advanced knowledge of the agent development life cycle and Spec Driven Development, including design and data analytics.
• Proven ability to lead product life cycle activities such as discovery, ideation, strategic development, requirements definition, and value management.
• Demonstrated experience with, or working understanding of, AI and agentic products or platforms, including foundational concepts such as LLMs and Harness.
• Hands-on experience using LLMs and AI-powered tools to improve personal and team productivity, with an instinct for where AI can address business and engineering problems.
• Ability to evaluate and instrument AI systems, with strong analytical skills to measure quality and performance for non-deterministic, agent-driven experiences.
• Proven track record delivering new product features through agile product development and the software delivery life cycle.
• Strong stakeholder management and interpersonal skills, with strategic thinking, thought leadership, and the ability to influence and align cross-functional partners.
• Bias for action and comfort operating in ambiguity in a dynamic, fast-evolving environment.
• Excellent written and oral communication skills.

Technologies

• Java
• Python
• Go
• Model Context Protocol (MCP)
• agent-to-agent (A2A)
• LLMs
• Harness

Preferred Qualifications, Capabilities, and Skills

• Hands-on experience building, maintaining, or driving adoption of agentic developer platforms, SDKs, or APIs, including a record of driving adoption with engineering audiences.
• Working knowledge of at least one of Java, Python, or Go, plus an understanding of what enables a multi-language SDK to be consistent and governable.
• Familiarity with open agent standards and protocols such as MCP and A2A, along with agent runtimes, tool-calling systems, and third-party agent development environments.
• Understanding of agentic patterns including orchestration, tool use, multi-step reasoning, and human-in-the-loop design, with an appreciation for balancing autonomy and guardrails.
• Awareness of Responsible AI principles, including safety, fairness, and governance, and comfort delivering AI products within a regulated environment.
• Experience benchmarking SDKs, runtimes, or developer platforms against internal targets and external frameworks to set roadmap priorities and measure parity and performance.
• Experience in a highly matrixed, complex organization, or experience in Financial Services or another highly regulated industry.

Location and Compensation

Seattle, WA 98101 (Onsite)

USD 133,000 - 215,000 per year

Benefits

• Comprehensive health care coverage
• On-site health and wellness centers
• Retirement savings plan
• Backup childcare
• Tuition reimbursement
• Mental health support
• Financial coaching