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Agent Building Blocks Technical Product Manager

Job in Seattle, King County, Washington, 98127, USA
Listing for: JPMorgan Chase & Co.
Full Time, Seasonal/Temporary position
Listed on 2026-10-17
Job specializations:
  • Software Development
    AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 140000 - 180000 USD Yearly USD 140000.00 180000.00 YEAR
Job Description & How to Apply Below
Agent Building Blocks Technical Product Manager

Seattle, WA, United States and 2 more

  • Job Identification
  • Job Category Product Management
  • Business Unit Corporate Sector
  • Posting Date 10/14/2026, 05:34 PM
  • Locations 1301 2nd Ave, Seattle, WA, 98101, US 3203 Hanover St, Palo Alto, CA, 94304, US 277 Park Ave, New York, NY, 10172, US
  • Job Schedule Full time
  • Job Shift Day
Job Description

Job Description

You enjoy shaping the future of product innovation as a product leader, driving value for customers, guiding successful launches, and exceeding expectations. Join our team to shape the future of enterprise agentic platform engineering by delivering a high-quality AI agent builder platform that engineers across the firm depend on every day.

As a Technical Product Manager on the AI Agents Platform, you help build the foundational developer platform that engineering teams use to design, build, test, register, deploy, monitor, and operate AI agents safely and at enterprise scale. This platform provides reusable components, runtime, and governance that enable teams to build and scale agentic experiences with speed, quality, and consistency.

In this role you own the reusable building blocks that every agent at the firm is assembled from: agent memory, harness as the firm-grade runtime for long-running agents, reusable agents such as NL2

SQL shipped as configurable templates, and the top connectors that let agents act in the systems people work in. You are accountable for converging fragmented, bespoke implementations onto shared, governed components that teams configure rather than rebuild, so the platform scales through reuse instead of per-team builds.

Job responsibilities

  • Develop a product strategy and vision for reusable agent building blocks, so teams compose governed, versioned components rather than rebuilding memory, runtime, and connectivity from scratch.
  • Own, maintain, and develop a product backlog across memory, harness, reusable agents, and top connectors that support the strategic roadmap and value proposition.
  • Engineer agentic memory as one governed memory-as-a-service platform with multiple constructs, including episodic and semantic recall with entitlement-aware scoping, enabled per use case.
  • Make the Harness the firm-grade runtime for long-running agents, and ship reusable agents as configurable templates on it rather than bespoke runtimes.
  • Drive reusable agents consolidation onto one platform, including a fine-tuned model in production and UI-based fine-tuning.
  • Execute the top-connector backlog, including connectors such as M365, Service Now, and Salesforce, and offer them to Directories as distributed, governed assets without duplicate builds.
  • Partner with data platform and engineering teams to deliver secure, governed access to structured, unstructured, analytical, and real-time data in line with firm data policy.
  • Build the framework and track key success metrics such as component reuse over bespoke builds, memory convergence, connector adoption, and reliability.
  • Capture the voice of the customer from lines of business and translate recurring needs into reusable components that serve many teams rather than one.
  • Own end-to-end delivery and execution, planning and prioritizing the backlog of supporting scrum teams.
  • Shape product strategy and vision as a thought leader who influences stakeholders across Technology, analytics, and the business and champions adoption of shared building blocks.

Required qualifications, capabilities, and skills

  • 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, design, and data analytics.
  • Proven ability to lead product life cycle activities…
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