Associate Vice President, Head of Enterprise AI Delivery

Merck & Co.; Rahway (NJ); Presencial; USD 250.000 - 450.000; Jornada completa

Descripción de la vacante

Merck & Co. seeks an executive leader to head Enterprise AI Delivery, coordinating non-engineering disciplines to convert AI strategy into measurable business outcomes. The role connects technology with divisions, balancing technical review credibility with divisional leadership perspectives.

Responsibilities span AI portfolio governance, operating model design, value realization, and collaboration on responsible AI across Legal, Privacy and Compliance.

Responsabilidades

• Facilitate enterprise AI demand intake, triage and prioritization to focus on high-value opportunities.
• Establish and run the delivery operating model for enterprise AI initiatives, including stage-gating, funding checkpoints, dependencies and delivery assurance.
• Maintain a single enterprise view of AI portfolio with scope, status, investment, risk and value; provide governance reporting.
• Partner with Division leadership to align AI investment with enterprise strategy and planning.
• Own the business case standard for AI investment, including baselining and evidence at each stage gate.
• Define post-implementation value measurement with Finance covering productivity, cycle-time, quality and cost benefits.
• Report realized value to executive governance, including initiatives that did not deliver.
• Collaborate with Legal, Privacy, Quality and Compliance on responsible AI framework and risk tiering.

Descripción del empleo

Job Description

The Associate Vice President, Head of Enterprise AI Delivery leads the business-facing capability that closes that gap. Reporting to the Chief AI Officer, this leader owns the non-engineering disciplines required to convert enterprise AI strategy into delivered, adopted and measured outcomes, organized into four functions: AI portfolio and value; process reengineering and operating model; enterprise AI products and delivery; and the AI Center of Excellence and adoption. This role is the connective tissue between our technology organization and the divisions it serves. The successful candidate will be equally credible in a technical design review and in a divisional leadership meeting, and will be measured not on what is built but on what changes as a result.

AI Portfolio & Value

• Facilitate the enterprise AI demand intake, triage and prioritization process, ensuring investment concentrations on the highest value opportunities.
• Establish and run the delivery operating model for enterprise AI initiatives, including stage-gating, funding checkpoints, dependency management and delivery assurance.
• Maintain a single enterprise view of the AI portfolio - scope, status, investment, risk and expected value - and provide the reporting that supports executive and Board-level governance.
• Partner with Division leadership and the enterprise strategy to align AI investment with the enterprise strategic plan and annual planning cycle.
• Own the business case standard for enterprise AI investment, including baselining, benefit definition and the evidence required at each stage gate.
• Establish and run post-implementation value measurement in partnership with Finance, including agreed treatment of productivity, cycle-time, quality and cost benefits.
• Report realized value to executive governance with rigor and candour, including initiatives that have not delivered.
• Collaborate with various business-side counterparts in Legal, Privacy, Quality and Compliance in the operation of the responsible AI framework, including use-case risk tiering and intake triage.

Process Reengineering & Operating Model

• Establish process and task mining as standard practice to document the actual as-is state, and build the internal capability to run it.
• Own quantitative baselining of every process entering the portfolio - cycle time, cost per transaction, touch points, handoffs, rework and defect rates - agreed with Finance at the outset, and maintain a prioritized portfolio sequenced on value, feasibility and risk.
• Lead task-level decomposition of priority processes, classifying each task as automatable, augmentable, irreducibly human on judgment or accountability grounds.
• Drive clean-sheet, AI-first redesign that starts from the required outcome, challenging steps that exist because of current capacity limits. Own control redesign as a first-class deliverable, reengineering the associated control.
• Conduct regulatory and validation impact assessment for every redesign touching a regulated process, covering Good Practice (GxP) requirements, computer system validation, audit trail and data integrity obligations, change control, and ongoing validation after release.
• Define the target operating model for each redesigned process - roles, decision rights, spans and layers, and where work sits - with the accountable business owner.
• Design the transition alongside the end state,