Lead Technical Program Manager

JPMorgan Chase JPMorgan Chase · Banking · OH · Corporate Sector

Lead the adoption and evolution of AI and LLM tooling within a Technical Program Management (TPM) function, owning the strategy for integrating AI agents into PM workflows, promoting automation, and upskilling the team. This role involves building and launching LLM-powered agents to automate tasks like status synthesis and risk flagging, defining prompt libraries and evaluation frameworks, and partnering with engineering for integration.

What you'd actually do

  1. Audit and Analyze existing PM workflows to identify automation opportunities and prioritize high-impact use cases.
  2. Own the AI Tooling Roadmap for the TPM function, from vision to execution.
  3. Build, Launch, and Iterate on LLM-powered agents that automate status synthesis, risk flagging, meeting notes, and more.
  4. Define and Maintain prompt libraries, evaluation frameworks, and best practices for LLM agent usage.
  5. Partner with Engineering to integrate AI agents into existing tools and delivery pipelines.

Skills

Required

  • 5+ years in Technical Program Management, Product Management, or a related field.
  • Hands-on experience with LLMs, prompt engineering, and API integrations.
  • Proven ability to partner with engineering teams to deliver technical solutions.
  • Strong analytical and systems thinking skills; able to audit and redesign workflows.
  • Experience driving change and influencing without direct authority.
  • Excellent communication skills; able to translate technical concepts for non-technical audiences.
  • Comfort with ambiguity, rapid iteration, and a fast-paced environment.

Nice to have

  • Familiarity with the SRE operating model and its interaction with Application Development teams
  • Familiarity with dashboarding and reporting tools such as Qlik Sense, QlikView, and Alteryx, with the ability to interpret data, track delivery and operational metrics, and support data‑driven decision making.
  • Strong working knowledge of JIRA (or equivalent tooling) to manage program backlogs, dependencies, milestones, risks, and delivery metrics across multiple teams and workstreams.

What the JD emphasized

  • own the end-to-end strategy for integrating AI agents into PM workflows
  • Build, Launch, and Iterate on LLM-powered agents
  • Define and Maintain prompt libraries, evaluation frameworks, and best practices for LLM agent usage

Other signals

  • Own the AI Tooling Roadmap for the TPM function, from vision to execution.
  • Build, Launch, and Iterate on LLM-powered agents that automate status synthesis, risk flagging, meeting notes, and more.
  • Define and Maintain prompt libraries, evaluation frameworks, and best practices for LLM agent usage.