VP AI Technology, Innovation & Delivery
Regeneron
September 03, 2026
On-site
Tarrytown, NY
IT
Core Responsibilities
- Defines and owns the enterprise AI architecture vision, design patterns, and technical standards across Regeneron; sets enterprise direction for agentic AI, evaluating/selecting platforms, frameworks, and architecture patterns.
- Determines where to build, buy, or partner for agentic AI capabilities; ensures strategic alignment with the GCC for build-and-operate execution.
- Translates business problems into solution blueprints, architecture patterns, and integration pathways; owns design decisions from concept through prototype with production-grade rigor.
- Leads product managers/product owners responsible for the enterprise AI portfolio: defined owners, roadmaps, and adoption metrics; treats AI solutions as products with measurable outcomes and sustained value.
- Tracks the AI frontier (models, platforms, agentic frameworks/methods) and translates insights into recommendations aligned to business and scientific priorities.
- Maintains view of AI progress in biopharma/life sciences; identifies use cases; runs structured pilots with clear adoption criteria.
- Stands up Forward Deployment Engineering: deploys cross-domain squads in rapid-configured GenAI/low-code modes and prototype-to-handoff engagements for higher-complexity problems.
- Defines squad model, deployment playbook, and engagement standards; builds a multidisciplinary org and partners with GCC leadership to ensure scalability, maintainability, and governed handoffs.
Qualifications
- BS/BA in a related field required.
- 20+ years leading applied AI/ML organizations end-to-end (opportunity identification, architecture, prototype, production handoff).
- Experience building/leading AI product management orgs (ownership, roadmaps, adoption accountability).
- Strong solution architecture depth and product mindset; ability to act as strategist and technical leader.
- Deep life sciences context; familiarity with generative AI, agentic systems, LLM application architecture, retrieval/reasoning patterns, modern AI/ML platforms.
- Hands-on low-code/no-code and configured GenAI deployment; know when to configure vs custom engineer.
- Track record scaling reusable AI capabilities in complex enterprises.
- Partnering with distributed teams; GCC India design-to-handoff experience strongly preferred.
- Ability to communicate/influence across stakeholders; strong people leadership and executive presence.
Application Instructions
- Apply now.
- Defines and owns the enterprise AI architecture vision, design patterns, and technical standards across Regeneron; sets enterprise direction for agentic AI, evaluating/selecting platforms, frameworks, and architecture patterns.
- Determines where to build, buy, or partner for agentic AI capabilities; ensures strategic alignment with the GCC for build-and-operate execution.
- Translates business problems into solution blueprints, architecture patterns, and integration pathways; owns design decisions from concept through prototype with production-grade rigor.
- Leads product managers/product owners responsible for the enterprise AI portfolio: defined owners, roadmaps, and adoption metrics; treats AI solutions as products with measurable outcomes and sustained value.
- Tracks the AI frontier (models, platforms, agentic frameworks/methods) and translates insights into recommendations aligned to business and scientific priorities.
- Maintains view of AI progress in biopharma/life sciences; identifies use cases; runs structured pilots with clear adoption criteria.
- Stands up Forward Deployment Engineering: deploys cross-domain squads in rapid-configured GenAI/low-code modes and prototype-to-handoff engagements for higher-complexity problems.
- Defines squad model, deployment playbook, and engagement standards; builds a multidisciplinary org and partners with GCC leadership to ensure scalability, maintainability, and governed handoffs.
Qualifications
- BS/BA in a related field required.
- 20+ years leading applied AI/ML organizations end-to-end (opportunity identification, architecture, prototype, production handoff).
- Experience building/leading AI product management orgs (ownership, roadmaps, adoption accountability).
- Strong solution architecture depth and product mindset; ability to act as strategist and technical leader.
- Deep life sciences context; familiarity with generative AI, agentic systems, LLM application architecture, retrieval/reasoning patterns, modern AI/ML platforms.
- Hands-on low-code/no-code and configured GenAI deployment; know when to configure vs custom engineer.
- Track record scaling reusable AI capabilities in complex enterprises.
- Partnering with distributed teams; GCC India design-to-handoff experience strongly preferred.
- Ability to communicate/influence across stakeholders; strong people leadership and executive presence.
Application Instructions
- Apply now.