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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Director - Artificial Intelligence, Machine Learning and Data Engineering - **Company:** CVS Health - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $144,200.0 - $288,400.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Big Data, Cloud Computing, Cloud Computing Security, Cloud Engineering, Cyber Security, Data as a Services, Information Engineering, Data Governance, Data Infrastructure, Data Transformation, Database Design, Disaster Recovery, Github, Identity and Access Management, Internet Security, Machine Learning, Metadata, Meta-Data Management, Microsoft Software, Software Tools, Azure Machine Learning, Search Technologies, Software Engineering, Enterprise Data Management, Privacy Controls, Cloud Platform System, Feature Engineering, Data Ingestion, Microsoft Power Automate, GitHub Copilot, System Availability, Generative AI, AI Platforms, Infrastructure Automation Frameworks, Deployment Automation, Data Management, Machine Learning Operations, Devsecops - **Published:** September 29, 2026 - **Apply:** https://www.careerbuilder.com/job-details/lead-director-artificial-intelligence-machine-learning-and-data-engineering-ct--f4e2dafc-8ae1-4e7d-93ad-64bfd2d8a4ab ## About the Role * 10+ years of experience in software engineering, data engineering, artificial intelligence, machine learning, platform engineering, or related engineering disciplines, including designing and delivering enterprise-scale technology solutions. * 7+ years of experience building and leading large-scale platform engineering organizations responsible for enterprise AI/ML platforms, data platforms, products, and technology delivery. * 7+ years of hands-on experience building and scaling AI/ML platforms, DevSecOps, MLOps, LLMOps, deployment automation, security engineering, and platform operations supporting mission-critical workloads. * 7+ years of experience designing and operating secure cloud-native platforms within highly regulated environments, including privacy, security, governance, compliance, identity management, audit controls, risk management, and operational resilience. * 5+ years of experience leading and developing high-performing engineering organizations, including Engineering Managers and senior technical professionals, while building enterprise Data Engineering capabilities, including large-scale data ingestion, batch and streaming architectures, data governance, and reusable data products., * Experience leading enterprise AI, Machine Learning, Data Platform, Platform Engineering, or Developer Platform organizations within healthcare, retail, financial services, technology, or other highly regulated industries. * Experience building and governing enterprise AI platforms utilizing Retrieval-Augmented Generation (RAG), GraphRAG, vector databases, foundation models, agentic architectures, MCP frameworks, and responsible AI capabilities. * Demonstrated success managing technology investments, platform portfolios, operating models, financial accountability, strategic vendor relationships, and executive stakeholder engagement. * Experience supporting large-scale platform modernization initiatives involving cloud-native architectures, platform engineering, developer enablement, enterprise data platforms, and AI/ML transformation programs. * Experience leveraging AI-powered engineering tools such as Claude, Claude Code, GitHub Copilot, Microsoft Copilot, and similar technologies to improve software development productivity, platform operations, engineering efficiency, and secure delivery practices., Bachelor's degree from accredited university or equivalent work experience (HS diploma + 4 years relevant experience)., Artificial Intelligence (AI), Auditing, Automation, Business Operations, Capacity Management, Cloud Architecture, Cloud Computing, Database Design, Disaster Recovery, Emerging Technology, Engineering Management, Enterprise Architecture, Establish Priorities, Executive Relationships, Financial Modeling, Financial Services, Geography, GitHub, Healthcare, Human Health, Identity Data Management, Incentive Programs, Internet Security, Investment Management, Leadership, MCP - Microsoft Certified Professional, Machine Learning, Memory Hardware, Metadata, Microsoft Product Family, Operational Measurement, Operational Strategy, Operational Support, Personal Care, Privacy Controls, Productivity Management, Quality Management, Retail, Risk Management, Safety/Work Safety, Security Infrastructure, Service Delivery, Software Development, Software Engineering, Standards Development, Strategic Analysis, Team Lead/Manager, Technical Delivery, Technical Leadership, Technical Strategy, Vendor/Supplier Planning, Vendor/Supplier Relations ## Description CVS Health is seeking a visionary and execution-focused Lead Director - Artificial Intelligence, Machine Learning and Data Engineering to build, scale, and operate enterprise capabilities that enable secure, reliable, responsible, and business-driven adoption of artificial intelligence across one of the largest healthcare organizations in the world. Within the Solutions Engineering and Infrastructure organization, this leader will play a critical role in establishing the foundational data, engineering, platform, governance, and operational capabilities required to deliver artificial intelligence and machine learning solutions at enterprise scale. Reporting to the Executive Director, this leader will oversee teams responsible for developing reusable data products, standing up platforms and components to accelerate AI solution delivery, launch developer enablement accelerators, establish DevSecOps/MLOps/LLMOps operational standards and frameworks for deploying and scaling agentic systems. This role combines deep technical expertise with demonstrated success leading large platform engineering organizations, driving enterprise transformation, delivering platform excellence, and developing high-performing teams., * Lead the strategy, architecture, and delivery of enterprise AI platform capabilities, including RAG, GraphRAG, vector search, MCP servers, memory and context services, reusable agents, model lifecycle management, and developer enablement accelerators that drive scalable AI/ML adoption. * Lead the strategy, development, and operation of reusable data products and enterprise data engineering capabilities, including data ingestion, transformation, quality, metadata management, lineage, feature engineering, and data services that support AI, analytics, and business outcomes. * Establish enterprise standards and operational practices for platform reliability, observability, infrastructure automation, security, privacy, compliance, model governance, responsible AI, risk management, disaster recovery, capacity planning, and audit readiness. * Partner with Architecture, Cybersecurity, Infrastructure, Product, Data, and Business leaders to guide technology strategy, evaluate emerging technologies, define enterprise standards, optimize investments, reduce duplication, and accelerate AI and data modernization initiatives. * Build, lead, and develop high-performing teams of Engineering Managers, Data Engineers, AI Engineers, Platform Engineers, and Operations Engineers while fostering a culture of innovation, accountability, continuous learning, inclusion, operational excellence, and measurable business impact. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [A Data Mesh needs Open Metadata](https://www.wearedevelopers.com/videos/505-a-data-mesh-needs-open-metadata) - [Coffee with Developers - Maria Apazoglou](https://www.wearedevelopers.com/videos/1209-coffee-with-developers-maria-apazoglou) - [Bringing AI Model Testing and Prompt Management to Your Codebase with GitHub Models](https://www.wearedevelopers.com/videos/1536-bringing-ai-model-testing-and-prompt-management-to-your-codebase-with-github-models) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Got AI ideas but no money? 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