Senior Director Acceleration Office Global Supply Chain Technology, MedTech

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and Med Tech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity.

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Technology Product & Platform Management

Multi-Family Technology Product & Platform Management

Professional

Raritan, New Jersey, United States of America

This is a remote/hybrid role available to the East Coast. While specific cities are listed in the Locations section for reference, please note that they are examples only and do not limit your application. We invite candidates from any location to apply.

Sr. Director, Med Tech Acceleration Office, Global Supply Chain Technology leads the design and execution of an AI-first, end-to-end delivery model that ensures all $2B+ transformation programs operate at peak effectiveness and realize their timeline, cost, and value objectives. This role creates a single accountable engine for orchestrating work streams, accelerating delivery, and maximizing measurable business impact from AI and automation.

Primary objective s:
Unifying disparate work streams into one orchestrated model is essential to unlock the full value of AI-enabled transformation: it reduces execution risk, shortens time-to-value, improves resource efficiency, and creates a repeatable playbook for future programs. The Senior Director provides the leadership and single-point accountability required to deliver those outcomes at scale.

• Establish a unified, end-to-end delivery model that removes handoff friction and aligns program, technology, and business work streams.
• Embed AI-first principles and automation into delivery practices so that decisions are data-driven and repeatable.
• Ensure consistent governance, portfolio-level visibility, and performance metrics across all major transformation programs.
• Prioritize and sequence the AI automation roadmap to deliver highest-value outcomes quickly and sustainably.
• Drive enterprise adoption and operationalization of new capabilities so value is captured and sustained.

• Owns delivery design, program management standards, and portfolio metrics for all $2B+ transformations.
• Coordinates cross-functional teams (IT, data science, process owners, legal/compliance, HR, finance, operations) to ensure integrated execution.
• Holds decision rights for delivery tradeoffs, prioritization of automation investments, and release sequencing within agreed governance.
• Escalates strategic risks and ensures alignment with executive sponsors and business unit leaders.

• Aligns transformation investments to strategic business priorities and measurable value drivers (revenue uplift, cost reduction, throughput, quality).
• Converts fragmented parallel initiatives into a cohesive orchestrated program that accelerates time-to-value and lowers program risk.
• Increases predictability of outcomes through standardized delivery playbooks, measurable KPIs, and a single source of truth for status and value capture.
• Key performance indicators:
  • Portfolio on-time delivery rate against milestone baselines.
  • Realized value vs. target (cost savings, revenue impact, productivity gains).
  • Percent of prioritized automation roadmap delivered and adopted.
  • Reduction in cross-workstream cycle time and handoff delays.
  • Stakeholder satisfaction and adoption metrics across impacted business units.

• Proactively identifies legal, regulatory, and data-governance exposures tied to AI/automation and coordinates mitigations.
• Maintains controlled change management to protect operational stability while accelerating capability rollout.
• Ensures clear accountability to avoid overlapping responsibilities and decision paralysis.

• Competency framework:
  Define the “AI-ready” competency model (technical, data literacy, product thinking, governance, ethics, change capability).
• Sourcing & staffing:
  Create prioritized pipelines for critical roles, including internal mobility and external hiring strategies.
• Learning & development:
  Launch modular learning pathways (foundations, role-based technical tracks, leadership for AI) and measure completion and proficiency.
• Performance & reward:
  Align performance goals, promotion criteria, and…