JPMorgan Chase
Agent Building Blocks Technical Product Manager
$133K–$215K
Seattle, WA +2 · Manager · Full-time · Posted Oct 14, 2026
- Location
- Seattle, WA
Palo Alto, CA
New York, NY - Experience
- 5+ years, or equivalent expertise, in AI product management or a relevant domain area.
About the job
Leads product strategy and delivery for reusable, governed AI agent building blocks—including memory, runtime, agent templates, and connectors—used by engineering teams across the firm.
What you'll do
- Develop the strategy, roadmap, and backlog for reusable agent components, and drive adoption in place of bespoke implementations.
- Deliver governed memory services, the Harness runtime, configurable reusable agents, and connectors; partner with data and engineering teams on secure data access.
- Lead end-to-end execution, prioritize supporting teams’ work, and track measures such as reuse, adoption, convergence, and reliability.
What they ask for
- 5+ years of experience or equivalent expertise in AI product management or a relevant domain area.
- Advanced knowledge of the agent development life cycle, Spec Driven Development, design, and data analytics.
- Experience or working understanding of AI and agentic products or platforms, including LLMs and Harness.
- Experience leading product life-cycle activities and delivering new features through agile product development and the software delivery life cycle.
Nice to have
- Experience managing reusable technology assets such as components, templates, connectors, or shared services.
- Understanding of agent memory, retrieval-augmented generation, connectors, fine-tuning, evaluation, and Responsible AI.
Pay
Seattle,WA $133,000.00-$215,000.00 USD base salary; Palo Alto,CA $133,000.00-$215,000.00 USD base salary; New York,NY $133,000.00-$215,000.00 USD base salary
Tools
LLMs, Harness, M365, ServiceNow, Salesforce, Snowflake, Databricks, NL2SQL
AI focus
Builds an enterprise platform for developing and operating AI agents, including agent memory, runtime, reusable agent templates, fine-tuning, connectors, evaluation, and governance.
Model-written summary · the original posting is authoritative