Distinguished Engineer- AI Agentics Engineeringing

At CVS Health, we're building a world of health around every consumer and surrounding ourselves with dedicated colleagues who are passionate about transforming health care.
As the nation's leading health solutions company, we reach millions of Americans through our local presence, digital channels and more than 300,000 purpose‑driven colleagues – caring for people where, when and how they choose in a way that is uniquely more connected, more convenient and more compassionate.
We do it all with heart, each and every day.

CVS Health is recruiting for a Distinguished Engineer – AI Agentics Engineering. In this high‑impact role, you will lead the architecture, design, and implementation of cutting‑edge autonomous AI agent systems that power intelligent automation across our enterprise operations. This role demands a systems thinker who thrives in complex multi‑agent environments, prioritizes agent orchestration and emergent behavior design over traditional ML model training.

You need to have a proven track record of building agentic systems from scratch. You will drive the evolution of AI agent platforms as a transformative paradigm while ensuring seamless integration with existing enterprise systems, autonomous decision‑making at scale, and intelligent orchestration across diverse business domains. You will serve as a thought leader and mentor for AI engineering teams, ensuring our agentic strategy is robust, innovative, and aligned with evolving business objectives.

Major

Responsibilities You will make an impact by: 1. Strategic Agentic Architecture & Design

• Drive the end‑to‑end architecture for highly scalable, multi‑agent systems that can operate autonomously across complex enterprise workflows, ensuring alignment with business goals and operational efficiency.
• Partner with other Principal Engineers, AI Architects, and executive leadership to shape the long‑term agentic roadmap, with specific milestones for agent capability expansion and cross‑domain integrations.
• Champion best practices for agent reliability, interpretability, safety, and performance optimization across all deployment environments.

2. Agent Platform Development & Orchestration

• Oversee the design and development of new AI agent platforms from the ground up, setting the standard for autonomous operation and intelligent coordination in large, complex enterprises.
• Implement robust agent lifecycle management, including spawning, monitoring, termination, and inter‑agent communication protocols for seamless scaling of autonomous services.
• Foster an engineering culture that values agent autonomy, emergent intelligence, and continuous learning capabilities.

3. Multi‑Agent Systems & Emerging AI Technologies

• Provide thought leadership on how multi‑agent systems, large language models, and reinforcement learning create unique demands on infrastructure, including real‑time decision engines, knowledge graph integration, and large‑scale agent coordination.
• Understand how to move AI agents from proof‑of‑concept to production‑ready autonomous systems.
• Evaluate and recommend emerging agentic technologies (e.g., tool‑using agents, reasoning frameworks, advanced planning algorithms) and guide their integration into the broader technology stack.

4. Cross‑Functional Leadership & AI Mentoring

• Serve as a key technical advisor for C‑level executives and product leaders, translating complex agentic architectural decisions into clear business value propositions.
• Mentor and coach senior AI engineers, data scientists, and operational teams, elevating the organization's overall agentic AI proficiency.
• Cultivate a strong, collaborative culture across distributed teams, promoting open communication, knowledge sharing, and responsible AI innovation.

5. Enterprise AI Governance & Safety

• Ensure adherence to AI ethics standards and responsible AI practices, advocating safety‑by‑design principles at every stage of the agent development lifecycle.
• Guide compliance with internal governance frameworks for AI explainability, bias mitigation, and autonomous system accountability.
• Identify risks in autonomous agent behavior and propose mitigation strategies in alignment with corporate…