Executive Director, AI Software Engineering (Principal)

Labcorp • Durham, NC

1d • $200 - $250 • Remote

About The Position

Labcorp is seeking a remote Executive Director, AI Software Engineering (Principal) to join our team! Location: Remote — United States Applicants who live within 35 miles of either the Burlington, NC or Durham, NC location will follow a hybrid schedule. This schedule includes a minimum of three in office days per week at an assigned location, either Burlington or Durham, supporting both collaboration and flexibility. Work Schedule: This is a full‑time, exempt (salaried) position assigned to a First Shift schedule, with standard business hours of Monday through Friday, 8:00 a.m. to 5:00 p.m. in your local time zone. Business needs may occasionally require flexibility in work hours, including earlier, later, or additional hours, with reasonable notice provided when possible. The Executive Director, AI Software Engineering (Principal) is a senior technology leader responsible for the vision, strategy, and execution of enterprise‑level applied AI engineering. This role oversees the development, scaling, and operationalization of AI systems that support Labcorp’s healthcare mission. The leader directs onshore and offshore engineering teams to deliver safe, compliant, and production‑ready AI solutions across clinical and enterprise workflows. This role shapes the architecture of AI platforms, mentors engineering leaders, aligns strategies across technical and business domains, and drives responsible AI adoption. The position operates at the intersection of research, product, engineering, and operations to bring applied AI to enterprise scale.

Requirements

• Bachelor’s degree
• 10 or more years of leadership experience in software engineering, AI engineering, or applied AI roles.
• 5 or more years experience building and operating production AI systems including model development, MLOps, deployment pipelines, and observability.
• 5 or more years experience designing prompt architectures, system prompts, and multi‑component prompt flows.
• 5 or more years experience implementing agentic patterns for orchestration, planning, and autonomous workflows.
• 5 or more years experience defining and applying AI safety, evaluation, monitoring, and alignment frameworks in enterprise environments.
• 5 or more years experience leading distributed engineering teams across onshore and offshore models.
• 5 or more years experience designing distributed systems and AI platform architecture for scalable, reliable services.
• 5 or more years experience working with security, compliance, or regulatory frameworks relevant to AI and data environments.
• Expertise in designing and scaling production AI systems.
• Understanding of AI and ML foundations including model types, training workflows, inference optimization, and evaluation practices.
• Skill in systems design, distributed architecture, and platform scalability.
• Proficiency in programming languages used across AI systems such as Python and backend languages.
• Understanding of data engineering, data pipelines, governance, and feature engineering for large‑scale AI workloads.
• Experience working within cloud platforms supporting AI compute, deployment, and monitoring.
• Ability to lead senior engineering talent and distributed teams.
• Strong communication skills for both technical and non-technical audiences.
• Ability to navigate trade-offs and influence cross-functional partners and executive stakeholders.
• Track record of end-to-end ownership of enterprise-level systems and services.
• Experience applying site reliability engineering practices to AI systems.
• Ability to drive predictable execution, improve delivery throughput, and enhance operational quality.
• Skill in creating documentation, architecture standards, and repeatable processes.
• Ability to identify emerging AI capabilities and translate them into practical engineering applications.
• Strong platform-building mindset focused on reuse, developer enablement, and long-term scalability.

Nice To Haves

• Masters degree in Computer Science, Data Science, or Artificial Intelligence.
• 5 or more years experience with AI and operational tools such as ServiceNow, observability platforms, event‑management systems, or cloud‑based AI services.
• 5 or more years experience with knowledge of retrieval‑augmented generation approaches and integration of retrieval into large language model‑based systems.
• 5 or more years experience maturing Agile and engineering processes within large organizations.

Responsibilities

• Strategic Leadership & AI Vision Define the long‑term strategy and roadmap for applied AI and AI engineering capabilities supporting enterprise healthcare goals. Ensure alignment between AI engineering initiatives and organizational priorities, system requirements, and operational needs. Represent AI engineering across executive forums and contribute to strategic planning and platform investments.
• AI Engineering Leadership & Execution Lead distributed engineering teams to deliver production‑grade AI systems with clear accountability and predictable execution. Oversee end‑to‑end development of AI systems including model lifecycle management, orchestration, deployment, and observability. Direct the design and implementation of prompt architectures, system prompts, agentic workflows, and intelligent automation patterns.
• AI Quality, Safety & Governance Establish frameworks for AI evaluation, monitoring, safety, alignment, and incident response to ensure responsible and compliant AI operations. Partner cross‑functionally with teams such as product, clinical, security, data, and legal to translate requirements into robust, validated solutions.
• Architecture & Platform Strategy Define architectural direction for scalable AI platforms, distributed systems, and model-serving infrastructure. Ensure reusable, secure, and developer-friendly AI platform components that support sustained enterprise adoption.
• Operational Excellence Implement engineering best practices across Agile delivery, documentation, estimation, SRE, QA, and development workflows. Ensure high availability, reliability, and operational performance of AI systems in production environments.
• Team Development & Leadership Recruit, develop, and mentor engineering leaders and senior-level individual contributors. Promote a culture of ownership, experimentation, quality, and continuous learning across teams.
• Vendor, Partnership & Budget Oversight Oversee vendor relationships, cloud usage, and external integrations to ensure optimization of cost, reliability, and operational efficiency.

Benefits

• Employees regularly scheduled to work 20 or more hours per week are eligible for comprehensive benefits including: Medical, Dental, Vision, Life, STD/LTD, 401(k), Paid Time Off (PTO) or Flexible Time Off (FTO), Tuition Reimbursement and Employee Stock Purchase Plan.
• Casual, PRN & Part Time employees regularly scheduled to work less than 20 hours are eligible to participate in the 401(k) Plan only.
• Employees who are regularly scheduled to work a 7 on/7 off schedule are eligible to receive all the foregoing benefits except PTO or FTO.

What This Job Offers

• Job Type: Full-time
• Career Level: Executive