Executive Director - Architecture & Advanced AI Engineering

Labcorp•Durham, NC

9h•Hybrid

About The Position

Labcorp is seeking an Executive Director, Architecture & Advanced AI Engineering, to lead enterprise architecture and advanced AI engineering. The role establishes scalable, secure, resilient, and reusable architectures and standards guiding platform, product, AI, and integration decisions. It leads teams that develop and deploy production AI capabilities, including models, agentic solutions, retrieval-augmented generation (RAG), and emerging technologies, and turns technology research and industry developments into scalable solutions with measurable business value. The position governs AI quality, safety, security, and responsible AI throughout development and deployment, and advances quality engineering, observability, cloud-first platforms, DevOps/SRE practices, backend engineering, and reliable production operations. It partners with business and technology leaders, influences senior stakeholders, and drives consistent standards, delivery excellence, and continuous improvement across complex initiatives. The role is based in Durham, North Carolina, with a hybrid work arrangement and 40–50% travel. It reports to the Senior Vice President of Platforms, AI & High Velocity Engineering.

Requirements

Bachelor’s degree.
At least 15 years of progressive experience in data, analytics, cloud, technology, platform engineering, AI, or digital transformation, including leadership of large-scale enterprise technology initiatives.
At least 10 years of people leadership, including responsibility for multidisciplinary teams, organizational strategy, execution, operational performance, talent development, and budget management.
At least 10 years defining and executing enterprise data, analytics, AI, cloud, or technology transformation strategies within large, complex, or highly regulated organizations.
At least 10 years leading enterprise-scale modernization initiatives involving cloud platforms, data ecosystems, enterprise architecture, AI/ML capabilities, and mission-critical technology services.
At least 10 years 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.
At least 10 years of experience with data governance, privacy, security, regulatory compliance, and responsible AI principles in healthcare or other highly regulated environments.
Ability to design and guide large-scale distributed enterprise architectures that balance business requirements, scalability, reliability, security, maintainability, and operational needs.
Deep knowledge of AI/ML engineering, including model development and evaluation, data pipelines, production deployment, performance monitoring, and enterprise-scale AI solutions.
Ability to establish quality, validation, safety, security, monitoring, and governance practices for responsible and reliable AI solutions.
Advanced knowledge of agentic architectures, orchestration patterns, RAG, and controls for reliable AI interactions with enterprise systems and users.
Strong understanding of reusable platforms, APIs, backend services, data stores, and engineering patterns that enable scalable capabilities and reduce duplication.
Advanced knowledge of cloud-native architecture, managed services, CI/CD, infrastructure automation, observability, incident management, and cost-effective production operations.
Ability to evaluate emerging AI, cloud, technology, and regulatory trends and translate relevant opportunities and risks into strategic initiatives, experiments, and roadmaps.
Ability to understand customer and business needs, translate workflows and pain points into technology priorities, and deliver solutions that support business outcomes.
Ability to establish quality indicators, improve delivery predictability, streamline processes, and drive continuous improvement across complex initiatives.
Ability to influence senior stakeholders, navigate competing priorities and technical trade-offs, resolve conflict, and build alignment around business-focused decisions.
Exceptional written and verbal communication skills, including communicating complex technical strategies, risks, recommendations, and decisions to technical and non-technical audiences.
Ability to establish architectural documentation, standards, runbooks, and playbooks that promote consistency, knowledge sharing, and adoption across teams.

Nice To Haves

MBA or advanced study in Computer Science, Data Science, Engineering, Information Technology, or Business Administration.
At least 10 years of experience in healthcare, diagnostics, life sciences, pharmaceutical, or other highly regulated industries.

Responsibilities

Define and lead enterprise and solution architecture strategy, establishing scalable, secure, resilient, and reusable architectures and standards for 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, 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 with measurable business value.
Establish and govern AI quality, safety, security, and responsible AI standards across development and deployment, including validation, monitoring, and risk controls.
Develop enterprise quality engineering and observability practices, including testing frameworks, automated validation, performance monitoring, and quality indicators.
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 technology solutions, and align architectural decisions with enterprise priorities.
Establish and promote architecture standards, technical documentation, reference designs, and playbooks to support consistent adoption of engineering and technology best practices.
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.
Assume end-to-end accountability for technology outcomes from strategy and architecture through delivery, operations, and continuous improvement.