[Hiring] Lead Director - Artificial Intelligence, Machine Learning and Data Engineering @CVS Health

Role Description

CVS Health is hiring a Lead Director - Artificial Intelligence, Machine Learning and Data Engineering to lead the strategy, delivery, and evolution of enterprise AI, data, and engineering capabilities that accelerate innovation across one of the largest healthcare organizations in the world. Reporting to the Executive Director, this leader will drive the development of enterprise platforms, reusable data products, and engineering capabilities that enable the successful adoption of emerging technologies and data-driven solutions across the organization.

The Lead Director of Artificial Intelligence, Machine Learning and Data Engineering will oversee teams responsible for AI platforms, data engineering, developer enablement, and cloud-native engineering solutions. This leader will guide the delivery of capabilities including:

• Retrieval-Augmented Generation (RAG)
• GraphRAG
• Vector search
• Agentic architectures
• MCP services
• Model lifecycle management
• Engineering accelerators that improve the speed, quality, and consistency of solution development

This role will also build and develop high-performing engineering teams while fostering a culture of innovation, accountability, collaboration, and technical excellence.

Qualifications

• 10+ years delivering enterprise software engineering, platform engineering, data engineering, artificial intelligence, machine learning, or related technology solutions within large-scale environments.
• 7+ years building and leading platform engineering, AI/ML platform, enterprise data platform, or developer platform organizations responsible for strategic technology delivery, operational excellence, and enterprise-scale platform adoption.
• 7+ years designing, implementing, and scaling AI/ML platforms utilizing technologies such as MLOps, LLMOps, deployment automation, observability, platform security, and mission-critical production operations.
• 7+ years architecting and operating cloud-native platforms within highly regulated environments, including governance, privacy, security, compliance, identity management, audit controls, risk management, and resiliency practices.
• 5+ years leading Engineering Managers and senior technical professionals while developing enterprise data engineering capabilities, reusable data products, large-scale data processing architectures, and modernization initiatives that drive measurable business outcomes.

Requirements

• Leadership of enterprise Artificial Intelligence, Machine Learning, Data Platform, Platform Engineering, Developer Platform, or Infrastructure Engineering organizations within healthcare, retail, financial services, technology, or other highly regulated industries.
• Demonstrated success building and governing enterprise AI platforms utilizing Retrieval-Augmented Generation (RAG), GraphRAG, vector databases, foundation models, agentic AI architectures, MCP frameworks, and responsible AI capabilities.
• Proven track record managing technology investments, platform portfolios, operating models, financial accountability, strategic vendor relationships, and executive stakeholder engagement.
• Background supporting large-scale modernization initiatives involving cloud-native architectures, platform engineering, enterprise data platforms, developer enablement, and AI/ML transformation programs.
• Familiarity with AI-assisted engineering tools such as GitHub Copilot, Microsoft Copilot, Claude, Claude Code, or similar technologies to improve engineering productivity, software delivery, platform operations, and developer experience.

Education

• Bachelor’s degree from accredited university or equivalent work experience (HS diploma + 4 years relevant experience).

Benefits

• Comprehensive benefits package designed to support the physical, emotional, and financial well-being of colleagues and their families.
• Medical, dental, and vision coverage.
• Paid time off.
• Retirement savings options.
• Wellness programs and other resources, based on eligibility.