Executive Director, Software Engineering AI Solutions

CVS Health

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Woonsocket, RI
Salary
$175,100–$334,750 / yr
Posted
3 days ago
Freshness
Confirmed live yesterday
Closes
Oct 12, 2026

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $232k
This role $255k
$156k most similar roles pay here $354k

This role pays more than 67% of similar roles. Most pay $195,687–$269,222 — the shaded band above. At the midpoint, this role pays about $255k versus about $232k for comparable roles.

Based on 240 similar postings.

Employer

About CVS Health

CVS Health is a leading American healthcare company operating retail pharmacies, pharmacy benefit management services, and a health insurance segment through Aetna, one of the nation''s largest health insurers. Industry: Healthcare & Pharmacy

CVS Health currently has 73 open roles on FindRole.

Listed pay typically runs $130,295–$284,280 across 72 roles with salary data.

Most-posted roles

View all roles at CVS Health

At a glance

TL;DR · Executive Director, Software Engineering AI Solutions

Executive Director, Software Engineering AI Solutions leads the design, development, and delivery of AI-powered software products and platforms to drive the Health100 strategy. Reporting to the VP of Engineering, this leader builds and scales a high-performing engineering organization focused on leveraging Generative AI and agentic technologies to solve complex healthcare and business challenges. The role involves defining technical strategy, establishing engineering excellence practices, and creating reusable frameworks and accelerators for rapid deployment. Key responsibilities include managing multiple teams, overseeing architecture governance, and ensuring the delivery of secure, scalable, and maintainable solutions. The position requires expertise in software architecture, APIs, microservices, DevSecOps, cloud-native platforms, and distributed systems. Candidates must possess experience with LLMs, conversational AI, intelligent workflow automation, and model governance to improve clinical workflows and operational efficiency within a healthcare context.

What you'll do

  • Lead the design, development, and deployment of AI-powered software products and platforms at enterprise scale.
  • Build and scale a high-performing engineering organization focused on Generative AI and agentic technologies.
  • Establish engineering best practices, architecture governance, and standards for secure, scalable, and maintainable software.
  • Develop reusable frameworks and accelerators to enable rapid delivery of AI use cases across the organization.
  • Identify emerging technologies and opportunities to create competitive advantages through AI-assisted capabilities and automation.
  • Recruit, mentor, and develop engineering leaders and technical talent within the department.
  • Translate business opportunities into production-grade software solutions in partnership with Product and Security teams.
  • Communicate engineering strategy, roadmaps, risks, and measurable outcomes to executive leadership.

What we're looking for

  • 15+ years of software development and technology leadership experience.
  • 10+ years leading large-scale engineering organizations.
  • 5+ years delivering AI, ML, or Generative AI solutions within enterprise software environments.
  • Experience building cloud-native platforms and distributed systems at scale.
  • Expertise in software architecture, modern engineering practices, APIs, microservices, DevSecOps, and cloud technologies.
  • Proven track record of leading organizations with 50+ engineers across multiple teams.
  • Strong executive communication and stakeholder management skills.
  • Experience building AI-native products from concept through production deployment (preferred).
  • Healthcare, pharmacy, payer, provider, or digital health experience (preferred).
  • Experience with LLMs, agentic architectures, conversational AI, and intelligent workflow automation (preferred).
  • Experience building internal platforms for enterprise-wide AI adoption (preferred).
  • Strong understanding of Responsible AI, model governance, and AI security (preferred).

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