Executive Director, Chief AI Architect

Labcorp is a global leader in laboratory services, providing the insights and answers that help healthcare providers, patients, researchers, pharmaceutical companies and health systems make confident decisions and improve outcomes. Through our unparalleled science, data, technology and laboratory network, we advance diagnostics, accelerate innovation and help address some of the world's most important health challenges. As we shape the future of healthcare, we are leveraging advanced technologies, intelligent digital solutions and data-driven innovation across our operations to enhance how work gets done and deliver greater value to customers and patients. With our global scale and deep expertise, you'll have the opportunity to do meaningful work, grow your career and make a real impact on people's health around the world. Together, we're improving health and improving lives.

Labcorp is seeking an Executive Director, Chief AI Architect, to join our team at Durham, NC.

Work Schedule: Work Schedule: Durham, NC / Hybrid | Full-time | Reports to: Chief AI Officer | Travel: 40-50%

Job Responsibilities

• Define and lead Labcorp's enterprise AI architecture strategy, standards, and roadmap.
• Drive AI architecture decisions across transformation programs, corporate functions, and enterprise platforms to maximize business value, scalability, and sustainability.
• Partner with business, product, engineering, data, and enterprise architecture leaders to embed AI capabilities into key initiatives.
• Establish and govern enterprise AI reference architectures, reusable patterns, and best practices for responsible AI adoption.
• Lead evaluation of emerging AI technologies, platform investments, and build-versus-buy decisions.
• Ensure AI solutions meet requirements for security, governance, quality, observability, and regulatory compliance.
• Measure and optimize AI outcomes including solution quality, adoption, operational efficiency, and cost effectiveness.
• Build and lead a high-performing AI architecture organization while developing AI architecture capabilities across the enterprise.

• Bachelor's degree.
• 15 or more years of experience in enterprise architecture, software architecture, AI/ML architecture, or technology leadership roles.
• 5 or more years of experience in healthcare, diagnostics, life sciences, pharmaceutical, payer, provider, or other regulated industries supporting solutions involving PII, PHI, compliance, and audit requirements.
• 5 or more years of hands-on AI experience, including production LLM, agentic, RAG, or AI-assisted development capabilities, with direct experience designing and shipping agentic systems in production

• Master's degree in computer science, Artificial Intelligence, Data Science or Engineering
• 5 or more years of experience designing and implementing enterprise AI platforms, agentic AI systems, retrieval-augmented generation (RAG), and multi-agent architectures.
• 5 or more years of experience with AI orchestration frameworks, agent protocols, vector databases, and multi-model AI ecosystems.
• 5 or more years of experience with enterprise knowledge graph platforms, semantic data models, ontologies, or semantic layer architectures.

• Demonstrated ability to influence enterprise technology strategy through partnerships with Enterprise Architecture, business transformation, and executive leadership teams.
• Demonstrated expertise evaluating emerging AI technologies, architectural patterns, and platform investments.
• Ability to establish and drive adoption of enterprise AI standards, reference architectures, and governance practices.
• Deep knowledge of modern AI architectures, including foundation models, agentic systems, retrieval-augmented generation (RAG), orchestration, evaluation frameworks, safety controls, observability, and production operations.
• Strong understanding of LLMOps practices, including model and agent lifecycle management, AI quality evaluation, observability, and cost optimization.
• Strong knowledge of security, privacy, identity, and governance requirements for AI solutions in regulated environments, including PII and PHI protections.
• Demonstrated ability to assess AI architecture tradeoffs based on business value, scalability, operational risk, production quality, and cost considerations.
• Recognized contributions to the AI architecture community through industry speaking, publications, advisory councils, or professional organizations.
• Proven ability to build, mentor, and lead high-performing architecture teams and communities of practice.
• Strong executive communication and stakeholder management skills across technical and non-technical audiences.