Director of AI Delivery Management

Merck•Rahway, NJ

5d•$173,200 - $272,600•Hybrid

About The Position

The Director of AI Delivery Management is part of the APEX engagement management and execution team and reports directly to the Executive Director of AI Delivery. The role plans, organizes, and executes end-to-end delivery of AI implementation projects and programs, establishes build teams for assigned engagements, and is accountable for successful delivery. It requires expertise across the software development lifecycle, AI technology, financial and people management, and large-scale techno-functional engineering delivery. The Director leads delivery execution and distributed teams; oversees product and portfolio management practices; supports demand intake, prioritization, governance, and investment decisions; and serves as a senior partner to clients and internal stakeholders. The role promotes ethical, safe, and value-driven AI, connects business needs to technical execution, and aligns strategic priorities with delivery capacity. It is accountable for measurable outcomes such as efficiency, growth, and patient outcomes, as well as engagement quality and stakeholder satisfaction. The position is hybrid, based primarily in Rahway, New Jersey. The posted base salary range for the primary location is $173,200–$272,600, with eligibility for an annual bonus and long-term incentive, if applicable. The company offers medical, dental, vision, and other insurance benefits, retirement benefits including a 401(k), paid holidays, vacation, and compassionate and sick days.

Requirements

Bachelor’s degree required.
At least 15 years of progressive leadership experience in software development roles, with a demonstrated trajectory to senior leadership.
At least 10 years leading managers or other people leaders across multiple functional teams and geographies.
At least five recent years delivering enterprise AI or intelligent automation solutions with measurable business impact.
Experience operating at scale in a large enterprise, including product/software lifecycle management and stakeholder engagement.
Strong familiarity with agile, product, and portfolio management practices and tools.
Exceptional senior-leader relationship-building and interpersonal skills, with the ability to influence IT and enterprise leadership.
Executive presence and ability to translate strategy into tactical execution.
Demonstrated thought leadership in AI strategy, product management, portfolio governance, and enterprise transformation.
Strong facilitation skills for workshops, ideation sessions, and executive briefings.
People leadership skills, including developing managers and fostering high-performing distributed teams.
Expert critical thinking and problem-solving skills, including the ability to explain complex technical and business trade-offs clearly and persuasively.
Proficiency in financial valuation, ROI analysis, and risk assessment for technology investments.
Excellent communication skills, including translating complex AI concepts for nontechnical audiences and producing clear written materials.
Skill in decision frameworks and governance design for prioritizing competing opportunities.
Experience managing teams across geographies.
Experience across the software development lifecycle, AI technology, financial management, people management, and large-scale techno-functional engineering delivery.
Strong background in agile methodologies, engagement lifecycle management, portfolio governance, customer engagement satisfaction, opportunity identification, harvesting engagement learnings, and establishing and building business cases.
Skills listed: AI implementation planning, artificial intelligence, AI ethics, critical thinking, data engineering, data visualization, enterprise leadership, lifecycle planning, organizational development, portfolio management, product management strategy, software configurations, software development, software development lifecycle (SDLC), and thought leadership.

Nice To Haves

Advanced degree preferred, such as an MBA, an MS in AI/ML or Computer Science, or a related field.

Responsibilities

Serve as the engagement execution lead for AI implementation projects, programs, initiatives, and strategic pursuits.
Represent the AI organization and provide executive counsel in cross-divisional IT planning, design, execution, and operations sessions.
Promote adoption of leading practices for ethical, safe, and value-driven AI in product development, portfolio management, and customer engagements.
Establish build teams for assigned engagements and oversee successful delivery.
Lead, mentor, recruit, develop, and retain AI team members, managers, employees, contractors, and high-potential practitioners.
Oversee multiple geographically dispersed teams across technology centers and foster servant leadership, psychological safety, inclusion, and continuous learning.
Ensure project and product management deliver product strategy, roadmaps, market and enterprise fit, and lifecycle management outcomes.
Champion agentic-led thinking and provide agentic management as a service to other divisions, promoting consistent, measurable, outcome-focused product practices.
Align product metrics to business value and ensure robust requirements, user-experience design, and go-to-market readiness.
Support demand management through intake triage, prioritization, valuation, transparency, and strategic alignment across the AI portfolio.
Apply prioritization frameworks and investment criteria that balance risk, return, strategic alignment, and capacity.
Ensure transparent project and program reporting, clear intake processes, and effective stage-gate governance for timely executive decisions.
Oversee engagement teams as the first-line AI consulting, awareness, and relationship-management function.
Drive high-quality stakeholder interactions, client satisfaction, and the volume and quality of inbound AI opportunities.
Promote consistent AI messaging, engagement methods, and workshop facilitation standards.
Apply AI frameworks to identify automation, optimization, and augmentation opportunities.
Develop documentation and design blueprints that connect business needs to technical execution.
Align strategic goals and business processes with AI delivery roadmaps.
Align engagement priorities with delivery capacity and be accountable for aggregate outcomes delivered by AI Delivery teams.
Monitor business impact, delivery health, and outcome achievement, ensuring AI initiatives result in measurable improvements to efficiency, growth, or patient outcomes.
Facilitate workshops, ideation sessions, and executive briefings that catalyze AI-led change.
Improve intake-to-delivery throughput, customer CSAT, divisional partner trust and satisfaction, and the flow of prioritized, well-scoped opportunities from Innovation Studios to Product and Delivery.