Executive Director Applied AI

Regeneron Pharmaceuticals•Tarrytown, GA

3d•$285,600 - $475,900•Hybrid

About The Position

Build our future together: 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. As a key member of our AI Technology, Innovation & Delivery team, this role leads Regeneron’s enterprise applied AI strategy and innovation agenda, accountable for translating frontier AI capabilities into production-grade solutions that advance the company’s scientific and business priorities. The Executive Director, Applied AI sets direction across four interconnected domains — Agentic AI Strategy and Platform Evaluation, Enterprise AI Product Management, Emerging Technology and Industry Intelligence, and Forward Deployment Engineering — and is responsible for moving from opportunity to architecture to deployed solutions. 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

Bachelor's degree (Master's or advanced degree preferred) with 17+ 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.
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.

Responsibilities

Sets enterprise direction for agentic AI, evaluating and selecting platforms, frameworks, and architecture patterns.
Leads a team of product managers and product owners accountable for Regeneron’s portfolio of enterprise AI capabilities.
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.
Leads a team that embeds directly with business and scientific stakeholders to activate AI solutions at speed.
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.
Set the technical and architectural direction for applied AI at Regeneron.
Translate business problems into solution blueprints, architecture patterns, and integration pathways.
Own design decisions from concept through prototype with the rigor required for production.
Lead the agentic AI strategy — defining where Regeneron builds, buys, or partners; and ensuring strategic alignment with GCC for build-and-operate execution.
Lead the Enterprise AI Product Management function — ensuring every enterprise AI capability has a defined roadmap, a business sponsor, and measurable adoption outcomes.
Lead the Forward Deployment Engineering function — maintaining a clear operational distinction between rapid-deployment mode and build-to-scale mode.
Connect emerging technology intelligence to specific business problems and scientific opportunities across all departments.
Run disciplined pilots with clear adoption criteria.
Partner with GCC engineering leadership to ensure solutions are buildable, scalable, and maintainable at platform level.
Define and govern handoff standards between applied AI prototypes and GCC production engineering.