Lead Technical Program Manager

JPMorgan Chase & Co.•Columbus, OH

About The Position

We are seeking an innovative and technically fluent AI/Automation Product Manager to lead the adoption and evolution of AI and LLM (Large Language Model) tooling within our Technical Program Management (TPM) function. As the “Builder” within the Technical Program Management function, you will own the end-to-end strategy for integrating AI agents into PM workflows, promoting automation, and upskilling the team.. This is a high-impact, high-visibility role at the heart of our organizational transformation. Be the architect of a next-generation, AI-augmented PM function and shape the future of how technical program management is done.

Requirements

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 Haves

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.

Responsibilities

Audit and Analyze existing PM workflows to identify automation opportunities and prioritize high-impact use cases.
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.
Partner with Engineering to integrate AI agents into existing tools and delivery pipelines.
Lead AI Upskilling sessions and create enablement materials for the TPM team.
Monitor and Report on adoption, usage, and impact metrics for AI tooling.
Champion Change Management and foster a culture of experimentation and continuous improvement.