Vice President, Engineering

LabConnect•Johnson City, TN

About The Position

The Vice President, Engineering provides strategic and operational leadership for software engineering, data architecture, and next-generation development platforms. This executive will lead the evolution of LabConnect’s technology organization toward an AI- and agentic-enabled engineering model, build the modern data foundation required to support scalable product innovation, and ensure delivery of secure, high-quality solutions that advance clinical trial operations.

Requirements

Bachelor’s degree in computer science, engineering, information systems, or a related field required; advanced degree preferred.
15+ years of progressive experience in software engineering and technology leadership, including a demonstrated track record of scaling high-performing teams and leading complex enterprise transformation initiatives.
Deep expertise in data architecture and data platform design, including practical understanding of relational, unstructured, blob, and vector-based data models and the trade-offs involved in applying them to enterprise software and AI-enabled solutions.
Significant experience leading large-scale technology and data initiatives in Microsoft Azure environments, including services such as Azure Data Lake, Synapse, Purview, and Cosmos DB.
Demonstrated success partnering with product leaders to balance platform modernization, technical debt reduction, and timely delivery of customer-facing capabilities.
Experience implementing modern software development practices, including AI-assisted engineering, intelligent automation, or emerging agentic development approaches.
Strong understanding of enterprise security, privacy, and compliance requirements, with experience partnering closely with security or SecOps leaders to deliver compliant, scalable solutions.
Strong executive presence with the ability to influence and build credibility across senior leadership, technical teams, and cross-functional stakeholders.
Exceptional communication skills, including the ability to translate complex technical concepts into clear, compelling messages for technical, operational, and executive audiences.
Strong judgment, agility, and initiative in ambiguous or rapidly evolving environments, with the ability to create alignment, structure, and momentum.
A contemporary understanding of software engineering and how AI-assisted development is reshaping planning, execution, testing, release management, and continuous improvement.
A proven ability to influence outcomes through collaboration, sound decision-making, and thoughtful organizational leadership.
The ability to operate strategically while engaging selectively and effectively in high-priority initiatives when needed.

Nice To Haves

Experience in regulated industries such as healthcare, life sciences, or clinical research strongly preferred.

Responsibilities

Lead the strategy and execution for a modern domain and data model that supports product scalability, operational efficiency, and AI-enabled use cases.
Oversee the evolution of legacy data environments into an integrated ecosystem of structured, unstructured, blob, and vector-based data architectures that enable secure and effective use of advanced models and automation tools.
Define and operationalize a modern engineering model in which human engineers and AI agents work together effectively.
Establish the structure, tooling, delivery rhythms, and team practices needed to move beyond traditional development approaches and increase speed, adaptability, and innovation.
Establish rigorous engineering, testing, release, and quality assurance practices that support the speed of AI-assisted development while maintaining the reliability, traceability, and performance expected in clinical trial technology environments.
Partner closely with product leadership to align architecture, platform investments, and engineering priorities with business goals, client needs, and product roadmaps.
Ensure technical decisions accelerate delivery of meaningful product outcomes and long-term platform value.
Collaborate with security and compliance leaders to ensure platforms, pipelines, and engineering practices are secure, resilient, and aligned with applicable healthcare, privacy, and quality requirements, including frameworks such as SOC 2, HIPAA, GDPR, and FDA 21 CFR Part 11.
Act as a key technical voice with executive leadership and, when appropriate, the Board, translating complex engineering, data, and AI concepts into clear business implications, opportunities, and risks.
Recruit, coach, and retain strong engineering and data leaders.
Establish clear performance expectations, accountability, and succession plans while fostering a culture of innovation, collaboration, and continuous improvement.