Lead Director, AI/ML & Data Engineering

CVS Health is a leading health care company dedicated to creating a more connected and compassionate health experience. They are seeking a Lead Director, AI/ML & Data Engineering to build and scale enterprise AI/ML capabilities, ensuring reliable and secure AI-powered platforms and solutions. This leadership role will oversee data engineering and AI/ML engineering disciplines, driving innovation and adoption across the organization.

Responsibilities:

• 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
• 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
• 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
• 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

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
• 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