This role pays less than
65%
of similar roles. Most pay
$202,800–$282,625
— the shaded band above.
At the midpoint, this role pays about
$216k
versus about
$243k
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
74 open roles
on FindRole.
Listed pay typically runs
$106,605–$260,590
across 72 roles with salary data.
Lead Director - Artificial Intelligence, Machine Learning and Data Engineering joins the Solutions Engineering and Infrastructure organization to build, scale, and operate enterprise capabilities for secure, reliable, and business-driven artificial intelligence adoption. This leader oversees teams developing reusable data products, infrastructure automation, and developer enablement accelerators while establishing DevSecOps, MLOps, and LLMOps standards for deploying agentic systems. Key responsibilities include managing the architecture of RAG, GraphRAG, vector search, MCP servers, and model lifecycle management alongside data engineering tasks like ingestion, transformation, and metadata management. The role requires expertise in cloud-native platforms within highly regulated environments to ensure compliance and risk management. Technical requirements include experience with foundation models, feature engineering, and AI-powered tools like GitHub Copilot or Claude. This position solves the challenge of scaling complex machine learning solutions across a large healthcare organization through robust platform engineering.
Lead the strategy, architecture, and delivery of enterprise AI platform capabilities including RAG, vector search, and model lifecycle management.
Oversee the development and operation of reusable data products and enterprise data engineering capabilities like ingestion, transformation, and metadata management.
Establish enterprise standards for platform reliability, security, privacy, compliance, and responsible AI governance.
Define DevSecOps, MLOps, and LLMOps operational frameworks to support the deployment and scaling of agentic systems.
Partner with cross-functional leaders to guide technology strategy, evaluate emerging technologies, and optimize investment portfolios.
Build and lead high-performing teams of engineers across data, AI, platform, and operations disciplines.
Drive large-scale platform modernization initiatives using cloud-native architectures and developer enablement tools.
What we're looking for
Must have 10+ years of experience in software engineering, data engineering, AI, machine learning, or platform engineering.
Must have 7+ years of experience building and leading large-scale platform engineering organizations for enterprise AI/ML platforms.
Must have 7+ years of hands-on experience with DevSecOps, MLOps, LLMOps, and deployment automation for mission-critical workloads.
Must have 7+ years of experience operating secure cloud-native platforms in highly regulated environments including privacy and compliance.
Must have 5+ years of experience leading engineering organizations and building enterprise data engineering capabilities like batch/streaming architectures.
Candidates must reside within the United States.
Bachelor’s degree from an accredited university or equivalent work experience (HS diploma + 4 years relevant experience).
Experience in highly regulated industries, advanced AI techniques like RAG, or managing technology investments is preferred.
Machine Learning
Large Language Models
Generative AI
Natural Language Processing
Python
SQL
Deep Learning
Model Evaluation
Clinical Data
EMR Systems
Data Science
Responsible AI
HIPAA
AI
ML
RAG
LLMs
Generative AI
Distributed Systems
Platform Engineering
Context Orchestration
Memory Systems
Retrieval Systems
Real-time Inference
Observability
System Optimization
Agent-based Systems
Data Engineering
AWS
Azure
GCP
AI
ML
MLOps
Data Lakes
Metadata Management
Distributed Data Systems
Data Quality
Enterprise Architecture
Software Engineering
Digital Platforms
Google Cloud
Vertex AI
BigQuery
GKE
Terraform
Kubernetes
GitOps
Pub/Sub
Dataflow
Cloud Run
OpenTelemetry
Microservices
Distributed Systems
DevSecOps
Retrieval-Augmented Generation
Service Mesh
Remote (Thousand Oaks, CA)6 days ago
$242,543–$328,146
Python
PyTorch
TensorFlow
JAX
MLOps
Generative AI
Foundation Models
Agentic AI
Azure
Databricks
Snowflake
AWS
Google Cloud
CI/CD
Data Engineering
Model Governance
Machine Learning
deep-learning