Associate Director Product Management - Enterprise AI

Regeneron Pharmaceuticals • Warren, MI

2d

About The Position

Regeneron’s newly established Enterprise Data & AI (EDAI) organization drives AI transformation and adoption across the enterprise. The Associate Director Product Management - Enterprise AI is a product leader for Regeneron’s AI platforms and tools, owning the roadmap for an assigned portfolio that enables colleagues to use AI, from internal assistants to secure data-connected applications and agentic solutions. The role translates business needs into technical requirements, frames decisions using explicit assumptions and analytical rigor, and uses data and user insight to identify opportunities and guide future capabilities.

The role also applies a forward deployed engineering approach, embedding with global development, business, and scientific teams to scope, prototype, and deploy AI and agentic solutions into production. It captures field feedback to inform platform roadmaps and codifies successful practices into reusable building blocks, playbooks, and reference architectures. The successful candidate works closely with the Chief AI Officer’s leadership team, the AI Innovation leader, Platform Engineering, Delivery Managers, and Business Unit IT partners to deliver useful, trusted, and widely adopted AI platforms.

The position owns product strategy and delivery for assigned platform components, supports technology evaluations and adoption, and partners with engineering teams—including GCC engineering teams—to turn architecture decisions and requirements into production-ready deliverables. It may involve hands-on contributions to prototypes, integrations, and evaluations when needed.

Requirements

• Bachelor's degree in a related field.
• 10+ years of progressive experience in technical product management.
• Strong working knowledge of large language models, foundation models, and generative AI, including capabilities, limitations, and evaluation.
• Familiarity with agentic AI, including autonomous and multi-step agents, tool use, planning and orchestration, and human-in-the-loop design.
• Hands-on understanding of interoperability standards, including Model Context Protocol (MCP) and Agent-to-Agent (A2A) protocols.
• Experience with retrieval-augmented generation (RAG), vector databases, embeddings, and grounding models in enterprise data.
• Familiarity with prompt engineering, context engineering, fine-tuning, and model customization.
• Understanding of AI evaluation and observability, including building evaluations, measuring quality and safety, monitoring drift, and managing model or agent performance in production.
• Awareness of responsible and secure AI practices, including guardrails, access controls, data privacy, and AI governance frameworks.
• Familiarity with MLOps/LLMOps tools and orchestration frameworks for building, deploying, and maintaining AI applications and pipelines.
• Ability to translate ambiguous business needs into clear product requirements and measurable outcomes.
• Ability to balance technical depth with product judgment and stakeholder empathy.
• Careful attention to detail and thoughtful scrutiny of data.
• Ability to build consensus across engineering, data science, business, IT, and Legal.
• Experience in embedded or customer-facing technical delivery, such as forward deployed engineering, solutions engineering, or applied AI prototyping.
• Hands-on engineering ability to prototype, integrate, and ship production-ready solutions, including contributing code when needed.
• Ability to scope and deliver complex deployments in ambiguous, fast-moving environments while balancing scope, speed, and quality.
• Comfort owning the roadmap, budget inputs, and outcomes for an assigned portfolio.

Nice To Haves

• Master's degree, MBA, or other advanced degree.

Responsibilities

• Own the release strategy and roadmap for an assigned portfolio of AI platforms and tools, aligned with the enterprise digital roadmap and EDAI platform strategy.
• Build business cases to develop, acquire, or invest in AI/ML capabilities, datasets, platforms, and tools.
• Prioritize competing demands and frame recommendations with clear assumptions and analytical rigor.
• Understand colleague and end-user pain points and identify high-value opportunities to improve their experience.
• Lead technical product development for assigned components of large-scale AI platforms, models, and supporting tools in partnership with engineering and Business Digital teams.
• Define requirements for platform capabilities including data access, model serving, search and ranking, automation pipelines, and self-service tools.
• Guide the use of cloud technologies to build and deploy automated ML and analytics pipelines.
• Evaluate, pilot, and deploy technologies using criteria established with product leadership.
• Drive product adoption by measuring usage, gathering feedback, and continuously improving products.
• Partner with GCC engineering teams to translate architecture decisions and product requirements into scoped, production-ready deliverables, maintaining alignment on priorities, handoffs, and delivery quality.
• Embed with business and scientific teams to scope, build, and deploy AI and agentic solutions from prototype through stable production.
• Own discovery, technical scoping, system design, and production rollout for priority deployments alongside BU IT and Platform Engineering.
• Contribute hands-on to prototypes, integrations, and evaluations when needed to make progress or clarify requirements.
• Evaluate and onboard AI model capabilities, including upgrades, tool use, and MCP-based integrations, against quality, safety, and cost criteria.
• Capture field feedback on model and platform performance and incorporate it into roadmaps and evaluation suites.
• Codify repeatable practices into reusable building blocks, playbooks, and reference architectures for business-unit adoption.

Benefits

• Annual bonuses or other incentive plans, depending on country and role.
• Equity awards, depending on country and role.
• Pension or retirement benefits, depending on country and role.
• 401(k) company match.
• Health and wellness programs.
• Fitness centers.
• Insurance benefits, including medical, dental, vision, life, and disability coverage.
• Paid time off.
• Family support benefits.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior