Technical Product Manager

Overall Purpose

The Technical Product Manager (TPM) for Product Engineering owns and drives the delivery of scalable, user‑centric applications that power P3’s clinical and operational workflows. This role sits at the intersection of software engineering, clinical operations, and business strategy — translating organizational priorities into well‑defined product requirements, release roadmaps, and delivery plans for our applications team. A critical and growing dimension of this role is leading the evaluation, integration, and operationalization of AI solutions enterprise‑wide.

This includes managing AI vendor relationships, designing and executing proofs of concept, and serving as the primary point of contact for employees as they adopt and scale AI‑powered tools in their day‑to‑day workflows. The TPM will partner closely with engineering leads, clinical stakeholders, and executive leadership to ensure applications are reliable, compliant, and aligned with our value‑based care mission.

• Own and manage the product backlog for the applications team, including creation, prioritization, and refinement of epics, features, and user stories aligned to clinical and operational workflows.
• Develop and maintain product roadmaps and delivery plans for the product engineering team, providing clear and consistent status updates to executive and operational stakeholders.
• Partner closely with software engineering leads to plan, execute, and deliver application initiatives on time and within scope.
• Serve as the primary liaison between business stakeholders, clinical operations, and the product engineering team — ensuring requirements are well‑understood, scoped, and delivered with clarity.
• Facilitate and participate in Agile ceremonies, including backlog grooming, sprint planning, and sprint reviews.
• Lead AI vendor evaluation and selection, including RFP processes, and ongoing vendor performance management against contractual commitments.
• Design, coordinate, and execute AI proofs of concept (POCs) in partnership with engineering, clinical, and operational stakeholders — establishing success criteria, measuring outcomes, and driving recommendations for production adoption.
• Serve as the primary internal point of contact for employees adopting AI tools — translating user feedback into product requirements, managing change enablement, and ensuring sustainable adoption across the organization.
• Maintain an AI solution inventory and integration roadmap, ensuring alignment with enterprise architecture, data governance, and compliance requirements.

• Knowledge of product management principles, product lifecycle management, and application delivery best practices.
• Understanding of software development lifecycle (SDLC) and Agile delivery methodologies in a product engineering context.
• Familiarity with modern application architectures, including APIs, cloud platforms, and SaaS integrations.
• Knowledge of backlog management, roadmap planning, and release coordination across cross‑functional teams.
• Understanding of Value Based Healthcare, provider enablement, and the clinical workflows that enterprise applications must support.
• Working knowledge of the AI vendor landscape, including large language models, AI‑powered workflow tools, and enterprise AI integration patterns.
• Ability to translate end‑user needs into AI solution requirements, define POC success criteria, and communicate outcomes to executive stakeholders.
• Strong change management and communication skills to drive employee adoption of new AI‑powered tools and workflows.

• 6–10 years of relevant experience, including roles in project management and/or business analysis, with a minimum of 2 years in a technical product management role focused on application or software product delivery.
• Proven experience managing multiple application products or portfolios across an organization, balancing competing priorities and diverse stakeholder groups.
• Hands‑on experience using tools such as Azure Dev Ops or Jira to manage product backlogs, plan sprints, and track delivery across engineering teams.
• Demonstrated experience leading AI…