Executive Director - Architecture & Advanced AI Engineering

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, Architecture & Advanced AI Engineering, to join our team in Durham, NC. Work Schedule: Durham, NC / Hybrid | Full-time | Reports to: Senior Vice President of Platforms, AI & High Velocity Engineering | Travel: 40-50% Job Responsibilities: Define and lead enterprise and solution architecture strategy, establishing scalable, secure, resilient, and reusable architectures and standards that guide platform, product, AI, and integration decisions. Build, lead, and develop high-performing Advanced AI Engineering teams responsible for production AI capabilities, including model development, agentic solutions, retrieval-augmented generation (RAG), and emerging AI technologies. Define and execute AI technology strategy and roadmaps, evaluating emerging capabilities and translating research, experimentation, and industry developments into scalable solutions that deliver measurable business value. Establish and govern AI quality, safety, security, and responsible AI standards across the development and deployment lifecycle, including appropriate validation, monitoring, and risk controls. Develop enterprise quality engineering and observability practices, including testing frameworks, automated validation, performance monitoring, and quality indicators that improve reliability and production readiness. Advance cloud-first engineering and platform capabilities through scalable architecture, DevOps/SRE practices, backend engineering standards, high availability, and cost-conscious technology decisions. Partner with business and technology leaders to simplify processes, translate business needs into effective technology solutions, and ensure architectural decisions align with enterprise priorities. Establish and promote architecture standards, technical documentation, reference designs, and playbooks that enable consistent adoption of engineering and technology best practices across teams. Influence senior stakeholders and facilitate decisions across complex initiatives, resolving architectural trade-offs, competing priorities, risks, and cross-functional dependencies. Drive engineering and delivery excellence through measurable quality standards, disciplined planning, improved predictability, and continuous improvement practices. Minimum Qualifications Bachelor’s degree 15 or more years of progressive experience in data, analytics, cloud, technology, platform engineering, AI, or digital transformation, including leadership of large-scale enterprise technology initiatives. 10 or more years of experience in people leadership, including responsibility for multidisciplinary teams, organizational strategy, execution, operational performance, talent development, and budget management. 10 or more years of experience defining and executing enterprise data, analytics, AI, cloud, or technology transformation strategies within large, complex, or highly regulated organizations. 10 or more years of experience leading enterprise-scale modernization initiatives involving cloud platforms, data ecosystems, enterprise architecture, AI/ML capabilities, and mission-critical technology services. 10 or more years of experience partnering with executive and C-suite stakeholders to align technology strategy and investments with business priorities, lead organizational change, manage risk, and deliver measurable business outcomes. 10 or more years of experience with data governance, privacy, security, regulatory compliance, and responsible AI principles within healthcare or other highly regulated environments. Preferred Qualifications MBA, Computer Science, Data Science, Engineering, Information Technology, Business Administration. 10 or more years of experience in healthcare, diagnostics, life sciences, pharmaceutical, or other highly regulated industries Additional Job Standards Enterprise Architecture & Systems Design: Demonstrated ability to design and guide large-scale, distributed enterprise architectures that balance business requirements, scalability, reliability, security, maintainability, and operational needs. AI Engineering & AI/ML Foundations: Deep knowledge of AI/ML engineering, including model development and evaluation, data pipelines, production deployment, performance monitoring, and enterprise-scale AI solutions. AI Quality, Safety & Governance: Demonstrated ability to establish quality, validation, safety, security, monitoring, and governance practices that support responsible and reliable AI solutions. Agentic AI & RAG: Advanced knowledge of agentic architectures, orchestration patterns, retrieval-augmented generation, and controls supporting reliable AI interactions with enterprise systems and users. Platform & Backend Engineering: Strong understanding of reusable platforms, APIs, backend services, data stores, and engineering patterns that enable scalable capabilities and reduce duplication across technology teams. Cloud, DevOps & Reliability Engineering: Advanced knowledge of cloud-native architecture, managed services, CI/CD, infrastructure automation, observability, incident management, and cost-effective production operations. Technology Strategy & Foresight: Demonstrated ability to evaluate emerging AI, cloud, technology, and regulatory trends and translate relevant opportunities and risks into strategic initiatives, experiments, and technology roadmaps. Customer & Business Acumen: Strong ability to understand customer and business needs, translate complex workflows and pain points into technology priorities, and deliver solutions that support meaningful business outcomes. Operational & Delivery Excellence: Demonstrated ability to establish meaningful quality indicators, improve delivery predictability, streamline processes, and drive continuous improvement across complex technology initiatives. Ownership & Leadership: Demonstrated ability to assume end-to-end accountability for technology outcomes, from strategy and architecture through delivery, operations, and continuous improvement. Stakeholder I