Delivery Success Leader, Enterprise Systems

Labcorp•Durham, NC

About The Position

The Delivery Success Leader, Enterprise Systems leads end-to-end delivery of complex technology projects, programs, and enterprise initiatives, ensuring alignment with business objectives and delivery of expected outcomes. The role establishes governance and delivery frameworks, develops roadmaps and resource plans, manages financials, and provides executive reporting. It applies Agile, Waterfall, or hybrid approaches and partners with business stakeholders, Product Owners, cross-functional teams, vendors, and technology partners to deliver measurable business value. The position also leads stakeholder engagement, organizational change management, adoption, training, and transition-to-support activities. It oversees service readiness and performance, manages risks and dependencies, and uses AI, automation, predictive analytics, and emerging technologies to improve planning, delivery, reporting, and operations. The role promotes accountability, collaboration, innovation, continuous improvement, operational excellence, and compliance with enterprise governance, security, regulatory, and Responsible AI standards. This is a full-time, exempt (salaried) position assigned to a first-shift schedule, with standard business hours Monday through Friday, 8:00 a.m. to 5:00 p.m. Business needs may occasionally require earlier, later, or additional hours, with reasonable notice when possible.

Requirements

Bachelor’s degree.
At least 8 years of progressive experience leading IT project delivery, delivery management, Agile program management, or related disciplines, including successful digital transformation, data, automation, and AI-enabled initiatives.
Demonstrated success delivering end-to-end projects and programs from initiation through implementation while driving adoption, value realization, and measurable outcomes.
Experience managing projects with both Agile and traditional project management methodologies.
Strong expertise in delivery orchestration, cross-functional team leadership, stakeholder engagement, dependency management, risk mitigation, resource coordination, and execution across multiple workstreams.
Experience leveraging AI-enabled tools and technologies to improve planning, reporting, documentation, forecasting, collaboration, workflow automation, decision-making, and delivery performance.
Hands-on experience supporting or delivering AI-enabled solutions, with understanding of AI lifecycle considerations including data readiness, governance, model dependencies, integration complexity, change management, adoption, and production deployment.
Ability to identify, evaluate, and implement automation opportunities that improve delivery efficiency, operational effectiveness, productivity, and business outcomes.
Proficiency with Jira, Confluence, Azure DevOps, or equivalent delivery and project management platforms.
Strong analytical, problem-solving, communication, facilitation, and presentation skills; ability to engage technical and non-technical stakeholders at all organizational levels.
Ability to influence without direct authority, build consensus, and drive alignment across business, technology, vendor, and leadership teams.
Ability to manage multiple concurrent projects, priorities, and deadlines in dynamic, fast-paced, evolving environments.
Experience establishing and reporting delivery success metrics, including schedule performance, adoption, value realization, operational improvements, customer impact, and strategic outcomes.
AI-forward mindset and interest in continuous learning, innovation, process improvement, emerging technologies, automation, and productivity-enhancing solutions.
Knowledge of laboratory operations, study design, and departmental equipment.
Ability to work independently and collaboratively within project teams.
Strong attention to detail and organizational skills.
Ability to lead complex technical programs and scientific initiatives.
Strong analytical and systems-thinking capabilities.
Effective communication and stakeholder engagement skills.
Experience in scientific computing, instrument control, and laboratory automation.
Ability to mentor and manage technical teams.
Commitment to quality, compliance, and continuous improvement.

Nice To Haves

At least 5 years of experience with Tableau and Alteryx.
SQL certification.
Tableau certification.
Six Sigma or Lean certification.

Responsibilities

Lead end-to-end delivery of complex technology projects, programs, and enterprise initiatives, ensuring alignment with business objectives, scope, schedule, budget, quality, and expected outcomes.
Establish and manage project governance, delivery frameworks, roadmaps, resource plans, business cases, financial forecasts, and executive reporting.
Drive execution using Agile, Waterfall, or hybrid methodologies and support predictable delivery and continuous value realization.
Partner with business stakeholders, Product Owners, and cross-functional teams to define requirements, prioritize work, and deliver measurable outcomes.
Facilitate Agile ceremonies, monitor delivery metrics, and improve team performance, productivity, and delivery maturity.
Manage project budgets, forecasts, cost controls, variance analysis, and benefits realization.
Build relationships with business leaders, executives, vendors, and technology partners, serving as a trusted advisor and delivery leader.
Provide executive communications, dashboards, governance updates, and data-driven recommendations.
Lead stakeholder engagement, organizational change management, user adoption, training, and transition-to-support activities.
Identify, assess, and mitigate risks, issues, dependencies, assumptions, and constraints.
Oversee service readiness, operational transition, service performance, SLA adherence, and continuous service improvement.
Use AI, automation, predictive analytics, and emerging technologies to improve planning, delivery efficiency, reporting, forecasting, and operational effectiveness.
Manage vendor relationships, contracts, delivery commitments, and resource capacity, ensuring accountability across contributing teams.
Collaborate with business, architecture, application, data, infrastructure, security, quality assurance, operations, and external partner teams.
Promote accountability, innovation, collaboration, continuous learning, operational excellence, and compliance with governance, security, regulatory, and Responsible AI standards.