Remote Lead: Enterprise AI/ML & Data Platform

Hispanic Alliance for Career Enhancement; Connecticut; Hybrid; USD 144,200 - 288,400; Full time

Job summary

CVS Health is seeking a visionary Lead Director for Artificial Intelligence, Machine Learning and Data Engineering to build enterprise AI capabilities at scale. You will lead teams delivering reusable data products, AI platforms, and governance frameworks, ensuring secure, compliant, and impactful AI solutions across the organization.

This U.S.-based remote role requires strong leadership of large platform teams, DevSecOps, and LLMOps, with a focus on measurable business outcomes and enterprise

Qualifications

• 10+ years of software/data/AI experience in enterprise settings.
• 7+ years building and leading large platform engineering organizations.
• 7+ years building and scaling AI/ML platforms, including DevSecOps/MLOps/LLMOps.

Responsibilities

• Lead enterprise AI platform strategy, architecture, and delivery (RAG, vector search, MCP servers, context services).
• Oversee reusable data products and enterprise data engineering capabilities for AI/analytics.
• Set standards for platform reliability, security, governance, and operations.
• Guide cross-functional collaboration with Architecture, Cybersecurity, Infrastructure, Product, Data and Business leaders.
• Build and mentor high-performing Engineering Managers and Engineers.

Skills

10+ years of experience

7+ years leading platform teams

7+ years scaling AI/ML platforms

7+ years cloud-native platforms

5+ years engineering leadership

Education

Bachelor's degree

Job description

CVS Health is seeking a visionary Lead Director for Artificial Intelligence, Machine Learning and Data Engineering to build enterprise AI capabilities at scale. You will lead teams delivering reusable data products, AI platforms, and governance frameworks, ensuring secure, compliant, and impactful AI solutions across the organization.

This U.S.-based remote role requires strong leadership of large platform teams, DevSecOps, and LLMOps, with a focus on measurable business outcomes and enterprise