Executive Director - High Velocity Engineering Platforms

Labcorp•Durham, NC

3d•Hybrid

About The Position

Labcorp is seeking an Executive Director, High Velocity Engineering Platforms, to join our team in Durham, NC. This role will lead the strategy, architecture, and delivery of enterprise AI engineering platforms, define and govern enterprise engineering frameworks, establish and advance developer experience capabilities, lead enterprise integration capabilities, architect and govern AI control plane capabilities, establish enterprise observability and operational standards, enable scalable data science and AI engineering capabilities, advance agentic AI engineering practices, develop and execute AI engineering and platform roadmaps, partner across Technology, Product, Data, Security, Privacy, Legal, and business functions, provide executive leadership for engineering organizations, and evaluate emerging AI technologies. The position requires a strong focus on operational excellence, including managing technical debt, reliability engineering, DevOps/SRE practices, platform performance, security, and continuous improvement.

Requirements

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 leading multidisciplinary teams, with responsibility for 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, analytics, interoperability, 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.
Expert-level proficiency across multiple programming languages, such as Python, Go, Java, and TypeScript, with the ability to understand, design, review, and provide strategic direction on complex codebases.
Advanced knowledge of production AI systems, including model deployment, inference optimization, lifecycle automation, scalability, reliability, and operational effectiveness.
Demonstrated ability to communicate complex technical strategies, recommendations, risks, and trade-offs to executive, technical, and business stakeholders and drive alignment across functions.
Strong understanding of developer and business user needs, with a product-oriented approach to designing platforms and capabilities that promote adoption and measurable business value.
Advanced knowledge of agentic AI design, orchestration patterns, lifecycle management, safety controls, and responsible approaches to developing and operating agent-based solutions.
Advanced knowledge of prompt engineering, system design, and practices that support reliable, controlled, and effective AI solutions.
Demonstrated ability to design and guide large-scale, modular platform architectures that balance scalability, extensibility, performance, reliability, and security.
Advanced knowledge of cloud platforms, managed services, cost optimization, and hybrid deployment models supporting enterprise-scale solutions.
Demonstrated ability to evaluate emerging technologies and industry trends, assess opportunities and risks, and translate insights into forward-looking platform strategies and investment priorities.

Nice To Haves

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.

Responsibilities

Lead the strategy, architecture, and delivery of enterprise AI engineering platforms that enable scalable, secure, reliable, and cost-effective AI capabilities across the organization.
Define and govern enterprise engineering frameworks, standards, tooling, libraries, CI/CD pipelines, runtime requirements, and developer experience patterns to ensure consistent and high-quality technology delivery.
Establish and advance developer experience capabilities, including reusable frameworks, templates, SDKs, and integrated workflows that accelerate solution development and improve time-to-value.
Lead enterprise integration capabilities, including APIs, connectors, and integration standards that enable reliable interoperability across applications, data platforms, AI services, and third-party technologies.
Architect and govern AI control plane capabilities, including policy enforcement, access management, model lifecycle controls, model provenance, security requirements, and operational controls.
Establish enterprise observability and operational standards, including Open Telemetry, service-level objectives, real-time monitoring, distributed tracing, dashboards, and incident response practices.
Enable scalable data science and AI engineering capabilities supporting experimentation, model deployment, feature management, inference, and production operations.
Advance agentic AI engineering practices by establishing lifecycle patterns, orchestration approaches, safety controls, and governance frameworks for enterprise agentic solutions.
Develop and execute AI engineering and platform roadmaps, establishing investment priorities, performance metrics, cost transparency, and technology strategies that accelerate business value.
Partners across Technology, Product, Data, Security, Privacy, Legal, and business functions to drive adoption, organizational change, governance, and compliance with enterprise standards.
Provide executive leadership for engineering organizations, including building and developing high-performing teams, managing budgets and resources, establishing KPIs, and representing platform strategy with senior leadership.
Evaluate emerging AI technologies, industry capabilities, opportunities, and risks and translate them into strategic platform investments and technology roadmap recommendations.
Promote operational excellence through effective management of technical debt, reliability engineering, DevOps/SRE practices, platform performance, security, and continuous improvement.