Lead Director, AI/ML & Data Engineering

CVS Health

1d • Remote

About The Position

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. POSITION SUMMARY CVS Health is hiring a Lead Director, AI/ML & Data Engineering to build and scale enterprise AI/ML capabilities that deliver reliable, responsible, and secure AI‑powered platforms and solutions at Fortune 5 scale. Our purpose is to deliver better health outcomes by meeting consumers where they are—through local care, digital experiences, and a nationwide team committed to quality, safety, and affordability. Within the Solutions Engineering and Infrastructure organization, this role is foundational to enabling AI adoption across CVS Health. The organization is responsible for enterprise‑scale AI/ML platforms that support mission‑critical workloads across the company. Reporting to the Executive Director, this leadership role is accountable for building and operating Data Engineering and AI/ML Engineering disciplines that enable enterprise AI/ML delivery at scale. You will lead product‑oriented engineering teams delivering reusable data products, AI platforms, and accelerators used across the enterprise. This is a U.S.-based REMOTE position; candidates must reside within the United States.

Requirements

• 10+ years of experience in software and/or data engineering, including large‑scale platform delivery; 5+ years leading managers and cross‑functional teams.
• Deep expertise in full‑stack and platform engineering in large‑scale, multi‑cloud environments.
• Advanced data engineering experience, including batch and streaming processing, data quality, metadata/lineage, and platform‑scale storage and query patterns.
• 8+ years building and operating Data Engineering, AI Engineering, DevOps, and MLOps capabilities supporting multiple product teams and mission‑critical workloads.
• Expert‑level knowledge of DevSecOps, MLOps, LLMOps, and GenAIOps operating models, tooling, and control planes (e.g., model registries, pipeline orchestration, deployment, monitoring).
• Extensive experience with secure cloud and hybrid platforms, Kubernetes, infrastructure‑as‑code, and enterprise identity and access management.
• 5+ years of experience operating in regulated environments with strong security, privacy, and audit requirements.

Nice To Haves

• Proven ability to lead product‑oriented platform teams and manage roadmaps, dependencies, and executive stakeholders.
• Experience managing budgets and vendor relationships for platform tooling, data services, and managed model or service providers.
• Experience establishing operating rhythms, performance metrics, and transparent reporting for delivery, platform health, and cost.
• Excellent written and verbal communication skills, with the ability to clearly articulate technical risk, cost, and value to senior leadership.

Responsibilities

• Data Engineering & Feature Enablement Build and scale enterprise data ingestion, transformation, and quality frameworks to support AI/ML use cases across IT operations, security, and business functions.
• Deliver reusable datasets, feature pipelines, and data products with strong metadata, lineage, privacy, and compliance controls.
• Partner with enterprise data, governance, and security teams to align stewardship models, data access patterns, and PHI/PII protections.
• Define and maintain data engineering standards, reference architectures, and operational playbooks.
• AI Engineering & DevSecOps Translate enterprise AI needs into scalable platform capabilities and reusable components (e.g., RAG frameworks, vector search services, evaluation harnesses, prompt libraries, reusable agents, model registries, and monitoring dashboards).
• Lead and mature DevSecOps practices for AI/ML, embedding security, automation, and compliance across the AI lifecycle.
• Drive cross‑functional alignment across security, infrastructure, architecture, and application teams to accelerate adoption and reduce duplication.
• Conduct technology assessments and proofs of concept to evaluate models, cloud services, and technical approaches.
• MLOps / LLMOps & Platform Operations Establish and operate enterprise MLOps, LLMOps, and GenAIOps platforms, including CI/CD for models and prompts, deployment automation, observability, and lifecycle governance.
• Own platform reliability and performance for model serving and AI application runtimes, including SLIs/SLOs, capacity planning, and on‑call readiness.
• Standardize production controls such as model versioning, canary deployments, rollback strategies, policy enforcement, and audit‑ready change management.
• People Leadership Recruit, retain, and develop high‑performing engineering managers and senior individual contributors.
• Build clear career paths and foster a culture of continuous learning and engineering excellence.

Benefits

• This full‑time position is eligible for a comprehensive benefits package designed to support the physical, emotional, and financial well‑being of colleagues and their families.
• The benefits for this position include medical, dental, and vision coverage, paid time off, retirement savings options, wellness programs, and other resources, based on eligibility.
• Additional details about available benefits are provided during the application process and on Benefits Moments.

What This Job Offers

• Job Type: Full-time
• Career Level: Director
• Number of Employees: 5,001-10,000 employees