Sr. Manager, AI Technical Product Manager

CVS Health•Work At Home-Connecticut, CT

1d•$130,295 - $260,590•Remote

About The Position

CVS Health delivers better health outcomes by meeting consumers where they are—through local care, digital experiences, and a nationwide team committed to quality, safety, and affordability. The Solutions Engineering and Infrastructure organization is building enterprise AI/ML capabilities that deliver reliable, responsible, and secure AI-powered platforms at Fortune 5 scale. Within this, the AI/ML Solutions Engineering and Delivery team operates as a Forward Deployment Engineering and Delivery Factory, embedding with IT Operations and Cybersecurity leaders to bring AI agent solutions from prototype to production. This Technical Product Manager (TPM) role reports to the Lead Director of AI/ML Solutions Engineering & Delivery and serves multiple AI agent delivery programs. You will operate at the intersection of product strategy and engineering execution, owning both product roadmap and engineering delivery. This is a Senior/Staff-level Individual contributor role requiring strong influence without authority, end-to-end ownership from scoping to go-live, and the ability to align cross-functional stakeholders while scaling delivery capacity. This role is Remote within the United States.

Requirements

7+ years of experience in Technical Product Management or Program Management delivering software, AI/ML, or automation products end-to-end, with ownership from concept through production release.
7+ years of experience delivering enterprise-scale AI/ML or automation solutions, with evidence of measurable impact (e.g., reduction in MTTR, cost savings, efficiency gains, or adoption KPIs).
7+ years of experience leading cross-functional teams without direct authority, including documented collaboration with engineering, architecture, security, and business stakeholders in a matrixed organization.
7+ years of experience working with technical systems, including: Reading/interpreting APIs, system architecture, or data flows Partnering with engineering teams to resolve blockers Reporting delivery metrics and program health to senior leadership
7+ years of experience in Agile/Scrum delivery environments, including: Backlog ownership and prioritization Sprint execution and ceremonies.
Hands-on use of Jira, Confluence, or equivalent tools
Bachelor’s degree from accredited university or equivalent work experience (HS diploma + 4 years relevant experience).

Responsibilities

Own end-to-end product delivery and roadmap execution: Drive product backlog, roadmap, release planning, and delivery across multiple AI agent programs supporting IT Operations automation and Cybersecurity intelligence.
Translate business requirements into epics, user stories, and acceptance criteria, lead prototypes through validation and transition successful solutions into scalable production systems or reusable components.
Drive cross-functional alignment and stakeholder engagement: Partner with IT Ops, Cybersecurity, Architecture, Security, Data Engineering, and Procurement leaders to define scope, validate use cases, and align on measurable success criteria (OKRs/KPIs).
Act as the primary point of contact for program status, roadmap decisions, and delivery outcomes, including executive-level communication and C-suite presentations.
Lead agile execution and delivery operations at scale: Serve as Scrum Master overseeing sprint ceremonies, team velocity, backlog prioritization, and blocker resolution.
Enforce strong agile and delivery discipline while evolving modern engineering practices for agentic systems.
Establish delivery playbooks, team norms, onboarding standards, and scalable operating models.
Own program performance, financials, and operational metrics: Define and track KPIs tied to operational efficiency, incident resolution, risk reduction, and adoption.
Manage product-level P&L, including budgets, vendor spend, and cost reporting.
Build dashboards and reporting cadences to provide leadership visibility into delivery health, risks, and outcomes.
Enable enterprise adoption and technical problem solving: Drive go-to-market strategies, change management, and user adoption to ensure delivered capabilities generate business value.
Resolve complex delivery challenges (API integrations, data dependencies, security requirements, system performance) while fostering reuse of shared AI components and coaching teams on delivery best practices.