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Executive Director, Agentic AI

Job in Sacramento, Sacramento County, California, 95828, USA
Listing for: CVS Health
Full Time position
Listed on 2026-03-09
Job specializations:
  • IT/Tech
    AI Engineer
Salary/Wage Range or Industry Benchmark: 125000 - 150000 USD Yearly USD 125000.00 150000.00 YEAR
Job Description & How to Apply Below

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time.

Role

Summary

The Executive Director, Agentic AI will define and lead the enterprise strategy, platform, and execution of Agentic AI systems —AI solutions capable of autonomous planning, reasoning, orchestration, and action across complex business workflows. This leader will be responsible for moving the organization from assistive AI to agent‑driven, outcome‑oriented intelligence , while ensuring trust, safety, governance, and regulatory compliance .

This role sits at the intersection of AI platform engineering, product strategy, architecture, and applied business transformation , and partners deeply with Digital Experience, Platforms, Integrations, Data, Security, Legal, and Operations.

Key Responsibilities 1. Agentic AI Strategy & Vision
  • Define the enterprise Agentic AI vision and roadmap, aligned to business outcomes (cost reduction, revenue growth, productivity, experience uplift).
  • Establish clear differentiation between LLM tools, copilots, workflows, and autonomous/multi‑agent systems.
  • Identify and prioritize high‑value agentic use cases (e.g., customer support resolution, claims/prior auth automation, contract leakage reduction, operational orchestration, developer productivity).
2. Agentic AI Platform & Architecture
  • Own the design and evolution of the Agentic AI Platform, including:
    • Multi‑agent frameworks (planner, executor, verifier, critic, retriever agents)
    • Tool/function calling and API orchestration
    • RAG, memory, state management, and context persistence
    • Human‑in‑the‑loop / human‑on‑the‑loop controls
  • Define standards for agent lifecycle management (design, testing, deployment, observability, rollback).
  • Partner with Digital Platform and Integration teams to ensure agents are API‑first, event‑driven, and scalable.
3. Applied AI Product Delivery
  • Lead delivery of production‑grade agentic solutions, not POCs.
  • Ensure agents are embedded into real digital experiences (chat, IVR, portals, internal tools).
  • Drive build‑once, reuse‑everywhere agent capabilities across channels and domains.
  • Establish clear success metrics: task completion rate, autonomy %, error rate, escalation rate, cycle‑time reduction.
4. AI Governance, Trust & Safety
  • Define and enforce Agentic AI governance frameworks, including:
    • Safety boundaries and guardrails
    • Explainability and auditability
    • Data privacy and security controls
    • Bias, hallucination, and failure‑mode mitigation
  • Partner with Legal, Risk, Compliance, and Security to ensure regulatory‑ready AI systems (HIPAA, SOC2, SOX, etc.).
  • Establish policies for autonomy thresholds and decision accountability.
5. Organization & Talent Leadership
  • Build and lead high‑performing AI engineering and applied science teams (staff, principal, managers).
  • Define role clarity across AI research, platform engineering, applied AI, and MLOps.
  • Coach leaders and teams on agentic system thinking vs traditional ML.
  • Drive a culture of responsible innovation, technical rigor, and business ownership.
6. Executive & Cross‑Functional Partnership
  • Act as the primary executive voice for Agentic AI with C‑suite and senior leadership.
  • Translate complex AI concepts into clear business narratives and investment cases.
  • Partner with Product, Experience, Operations, and Business leaders to co‑own outcomes.
  • Represent the company externally with partners, vendors, and industry forums.
Required Qualifications
  • 12+ years in software engineering, platforms, or AI/ML, with 5+ years in senior leadership roles.
  • Hands‑on experience delivering AI systems at enterprise scale (not just experimentation).
  • Deep understanding of:
    • LLMs, SLMs, RAG, embeddings, vector databases
    • Agent frameworks and orchestration patterns
    • Distributed systems, APIs, event‑driven architectures
  • Proven ability to operate in regulated, high‑availability…
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