VP AI Technology, Innovation & Delivery

Regeneron Pharmaceuticals•Tarrytown, GA

4d•Onsite

About The Position

Regeneron’s Enterprise Data & AI organization is newly established and moving fast — built to drive AI transformation and adoption at scale across every part of the enterprise. This is a high-visibility, high-velocity position where the work is directly tied to business and scientific impact. The Vice President, AI Technology, Innovation and Delivery is the first hire into this function. This leader establishes Regeneron's AI architecture foundation, stands up the engineering capability, and builds the practice before leading it. Accountable for translating frontier AI capabilities into production-grade solutions, this role defines the enterprise AI architecture vision, stands up Forward Deployment Engineering, and owns the AI innovation engine from horizon scanning to proof-of-concept to scaled deployment. As the organization matures, this leader will lay the groundwork for future sub-function leaders across architecture, engineering, and innovation. The role works in close partnership with the Data & AI Engineering leader in Regeneron’s Global Capability Center (GCC) in India, where build and operate resides. Together, they ensure that what is designed is architected for platform-scale delivery and built to last.

Requirements

BS/BA degree in a related field required.
20+ years leading applied AI/ML organizations through the full lifecycle — opportunity identification, architecture, prototype, and production handoff.
Demonstrated experience building and leading AI product management organizations — establishing product ownership, roadmaps, and adoption accountability for enterprise AI capabilities.
Strong product mindset paired with hands-on solution architecture depth; able to operate as both strategist and technical leader — not a pure people-manager.
Deep appreciation for the life sciences context — an understanding of how AI is reshaping drug discovery, clinical development, regulatory, and commercial functions in biopharma, and a genuine appetite to engage with Regeneron’s science. This orientation is essential to earn credibility with Regeneron’s scientific and operational leadership.
Deep familiarity with the current AI landscape: generative AI, agentic systems, LLM application architecture, retrieval and reasoning patterns, and modern AI/ML platforms.
Hands-on familiarity with low-code/no-code AI deployment and configured GenAI platforms; able to recognize when a business problem calls for rapid configuration versus custom engineering and build a team that executes both modes with equal discipline.
Proven track record building and scaling reusable AI capabilities across a complex enterprise.
Experience partnering with distributed engineering organizations; successful experience designing-to-handoff with a GCC team in India or similar global delivery model is strongly preferred.
Ability to communicate and influence effectively across Digital Technology groups, business units, and the GCC team in India.
Strong people leadership; experience leading leaders and building senior technical organizations in a competitive market.
Demonstrated executive presence and enterprise influence. Track record shaping AI strategy at the senior leadership level and building organizational credibility across scientific, commercial, and technology functions.

Nice To Haves

Successful experience designing-to-handoff with a GCC team in India or similar global delivery model is strongly preferred.

Responsibilities

Defines and owns the enterprise AI architecture vision, design patterns, and technical standards across Regeneron. Sets enterprise direction for agentic AI, evaluating and selecting platforms, frameworks, and architecture patterns. Strategy and platform selection reside in this role; build and operate sit within the GCC.
Determines where Regeneron builds, buys, or partners for agentic AI capabilities, ensuring strategic alignment with the GCC for build-and-operate execution.
Translates business problems into solution blueprints, architecture patterns, and integration pathways, owning design decisions from concept through prototype with production-grade rigor.
Leads a team of product managers and product owners accountable for Regeneron’s portfolio of enterprise AI capabilities. Each capability has a defined owner, a roadmap, and adoption metrics, ensuring AI solutions are treated as products, not projects: with clear business sponsors, measurable outcomes, and a path to sustained value.
Tracks the AI frontier across models, platforms, agentic frameworks, and methods, and translates that intelligence into concrete recommendations tied to Regeneron’s business and scientific priorities.
Maintains a clear view of how AI is advancing across biopharma and life sciences and identifies where emerging capabilities can solve real problems or unlock new opportunities. Runs structured pilots with clear adoption criteria.
Stands up Regeneron’s Forward Deployment Engineering capability from the ground up. Deploys cross-domain squads that embed directly with business and scientific stakeholders to accelerate priority use cases. Operates in two modes: rapid deployment of configured GenAI and low-code/no-code solutions and structured prototype-to-handoff engagements for higher-complexity problems requiring GCC production engineering.
Defines the squad model, deployment playbook, and engagement standards, establishing the operational distinction between rapid-deployment and build-to-scale modes from day one.
Builds, develops, and leads a multidisciplinary organization spanning product managers, applied AI engineers, solutions architects, and forward deployment engineers. Sets the technical bar, develops senior talent, and holds the organization to measurable outcomes.
Partners with GCC engineering leadership to ensure solutions are buildable, scalable, and maintainable at platform level. Defines and governs handoff standards between applied AI prototypes and GCC production engineering.
Represents applied AI to senior leadership across the enterprise. Partners with peers across Enterprise Data & AI to ensure delivery is integrated with data, MLOps, and governance functions.