Lead Director - Artificial Intelligence, Machine Learning and Data Engineering
CVS Health · Hartford, CT · 3 wk ago
RemoteRemoteEngineering$144k/yrFull-time
We need to output HTML fragment with sections: About the role? The posting includes a paragraph about building world of health etc. That's like an intro. Could be "About the role" or maybe "Position Summary". The instructions: use for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). We should include sections only when posting has real specific content. We have:
- Intro paragraph: "We’re building a world of health..." That's like about the company/mission. Could be "About the role"? Might be better as "About the role" or maybe "Position Summary". The instructions list example headings; we can choose appropriate. The posting includes "Position Summary" heading. So we can use that as a section heading (
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). We should include sections only when posting has real specific content. We have:
- Intro paragraph: "We’re building a world of health..." That's like about the company/mission. Could be "About the role"? Might be better as "About the role" or maybe "Position Summary". The instructions list example headings; we can choose appropriate. The posting includes "Position Summary" heading. So we can use that as a section heading (Position Summary
) with the paragraph(s) under it.
- Primary Duties And Responsibilities: list of duties. Use Responsibilities
with - items.
- Required Qualifications: list. Use
Qualifications
(or Requirements). The instructions list Requirements, Qualifications, Skills. We have Required Qualifications and Preferred Qualifications. Could combine into Qualifications section with required and preferred? But better to separate? The instruction: prefer a few substantive sections over many thin ones. Could have Qualifications (including required and preferred) as one section. But we need to preserve all info. Could have Required Qualifications
and Preferred Qualifications
as separate headings? Those are not in the example list but we can still use them? The instruction says use for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It doesn't forbid other headings, but suggests those as examples. Safer to stick to those. We could map Required Qualifications to Qualifications
and include both required and preferred bullet lists under it, maybe with subheadings? But we cannot add extra headings inside? Could use
to label required vs preferred. Simpler: have
Qualifications
then two paragraphs: one for required, one for preferred, each with
- . That preserves info.
- Education: could be part of Qualifications as well. Could include under Qualifications.
- Pay Range: we have pay range info. So include
Pay
with containing the pay range details.
- Benefits: we have benefits description. Include
Benefits
with .
- Schedule: not mentioned besides "U.S.-based REMOTE position". Could include Schedule? Not given. So omit.
- About the role: we have intro paragraph about mission. Could be
About the role
with that paragraph.
We must not repeat job title as heading. Not include Job ID etc. Remove boilerplate like EEO, etc. Also remove application instructions (like "Qualified applicants with arrest...") and "We anticipate the application window..." etc. Also remove "EDUCATION" heading? We'll incorporate education into Qualifications.
We must preserve all substantive information. Let's extract content.
Intro paragraph: "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 paragraph(s): after "Position Summary 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. This is a U.S.-based REMOTE position; candidates must reside within the United States."
Primary Duties And Responsibilities: list items (separated by periods but each starts with a capital letter and seems like separate duty). Let's extract each bullet:
- 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.
Required Qualifications: list items:
- 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.
Preferred Qualifications: list items:
- 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.
Education: "Bachelor’s degree from accredited university or equivalent work experience (HS diploma + 4 years relevant experience)."
Pay Range: paragraph: "The Typical Pay Range For This Role Is $144,200.00 - $288,400.00 This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls. The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors. This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above. This position also includes an award target in the company’s equity award program."
Benefits: paragraph: "Our people fuel our future. Our teams reflect the customers, patients, members and communities we serve and we are committed to fostering a workplace where every colleague feels valued and that they belong. Great Benefits For Great People We take pride in offering a comprehensive and competitive mix of pay and benefits that reflects our commitment to our colleagues and their families. 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."
We should remove the line about application window closing etc. Also remove EEO etc. Also remove "Qualified applicants with arrest or conviction records will be considered..." etc.
Now construct HTML.
We'll have:
About the role
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 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. This is a U.S.-based REMOTE position; candidates must reside within the United States.
Responsibilities
- 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 Man
Qualifications
(or Requirements). The instructions list Requirements, Qualifications, Skills. We have Required Qualifications and Preferred Qualifications. Could combine into Qualifications section with required and preferred? But better to separate? The instruction: prefer a few substantive sections over many thin ones. Could have Qualifications (including required and preferred) as one section. But we need to preserve all info. Could haveRequired Qualifications
andPreferred Qualifications
as separate headings? Those are not in the example list but we can still use them? The instruction says use for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It doesn't forbid other headings, but suggests those as examples. Safer to stick to those. We could map Required Qualifications to Qualifications
and include both required and preferred bullet lists under it, maybe with subheadings? But we cannot add extra headings inside? Could use
to label required vs preferred. Simpler: have
Qualifications
then twoparagraphs: one for required, one for preferred, each with
- . That preserves info.
- Education: could be part of Qualifications as well. Could include under Qualifications.
- Pay Range: we have pay range info. So include
Pay
withcontaining the pay range details. - Benefits: we have benefits description. Include
Benefits
with. - Schedule: not mentioned besides "U.S.-based REMOTE position". Could include Schedule? Not given. So omit. - About the role: we have intro paragraph about mission. Could be
About the role
with that paragraph. We must not repeat job title as heading. Not include Job ID etc. Remove boilerplate like EEO, etc. Also remove application instructions (like "Qualified applicants with arrest...") and "We anticipate the application window..." etc. Also remove "EDUCATION" heading? We'll incorporate education into Qualifications. We must preserve all substantive information. Let's extract content. Intro paragraph: "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 paragraph(s): after "Position Summary 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. This is a U.S.-based REMOTE position; candidates must reside within the United States." Primary Duties And Responsibilities: list items (separated by periods but each starts with a capital letter and seems like separate duty). Let's extract each bullet: - 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. Required Qualifications: list items: - 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. Preferred Qualifications: list items: - 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. Education: "Bachelor’s degree from accredited university or equivalent work experience (HS diploma + 4 years relevant experience)." Pay Range: paragraph: "The Typical Pay Range For This Role Is $144,200.00 - $288,400.00 This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls. The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors. This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above. This position also includes an award target in the company’s equity award program." Benefits: paragraph: "Our people fuel our future. Our teams reflect the customers, patients, members and communities we serve and we are committed to fostering a workplace where every colleague feels valued and that they belong. Great Benefits For Great People We take pride in offering a comprehensive and competitive mix of pay and benefits that reflects our commitment to our colleagues and their families. 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." We should remove the line about application window closing etc. Also remove EEO etc. Also remove "Qualified applicants with arrest or conviction records will be considered..." etc. Now construct HTML. We'll have:About the role
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 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. This is a U.S.-based REMOTE position; candidates must reside within the United States.
Responsibilities
- 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 Man