Associate Director Product Management - Enterprise AI

Associate Director Product Management - Enterprise AI

Enterprise Data & AI | Tarrytown, NY

ROLE SUMMARY

Regeneron’s newly established Enterprise Data & AI organization is 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 product leader for Regeneron's AI platforms and tools, the successful candidate will have the potential for massive impact and help shape how the enterprise builds, accesses, and adopts AI capabilities. The Associate Director Product Management - Enterprise AI will own the roadmap for a defined portfolio of enterprise platforms and tools that put AI into the hands of colleagues across the organization, from internal AI assistants to secure data-connected applications to agentic solutions. They will translate business needs into clear technical requirements, frame decisions with a transparent view into their assumptions and the rigor behind them and proactively use data to inspire the next generation of capabilities.

The role also applies a forward deployed engineering approach, embedding with global development and business unit teams to deploy AI and agentic solutions into production and returning field signal to shape the platform roadmap.

The successful candidate will be an integral member of the Enterprise Data & AI (EDAI) team, and will work closely with the Chief AI Officer’s leadership team, the AI Innovation leader, the Platform Engineering team, Delivery Managers, and Business Unit IT partners. Together the team will leverage Regeneron's rich data and state-of-the-art infrastructure to deliver platforms that are useful, trusted, and adopted at enterprise scale.

As Associate Director Product Management - Enterprise AI, a typical day might include the following:

Product Strategy & Roadmap

Own the release strategy and roadmap for an assigned portfolio of Regeneron's AI platforms and tools, aligned to the enterprise digital roadmap and the EDAI platform strategy

Build business cases to develop, acquire, or invest in new AI/ML capabilities, datasets, platforms, and tools

Prioritize ruthlessly across competing demands, framing recommendations with clear assumptions and analytical rigor.

Develop deep insight into colleague and end-user pain points and identify the highest-value opportunities to improve their experience.

Platform & Tools Delivery

Lead the technical product development of assigned components of large-scale AI platforms, machine learning/AI models, and supporting tooling, partnering with engineering and Business Digital teams to ship high-quality deliverables.

Define requirements for core platform capabilities: data access, model serving, search/ranking, automation pipelines, and self-serve tools.

Guide the use of cloud technologies (AWS, Azure, GCP) for building and deploying automated ML and analytics pipelines.

Run evaluation, pilot, and deployment of new technologies against the framework and criteria set with product leadership, building toward an industry-leading internal AI ecosystem.

Drive product adoption: measure usage, gather feedback, and continuously improve.

Partner with GCC engineering teams to translate platform architecture decisions and product requirements into well-scoped, production-ready deliverables; maintain ongoing alignment on roadmap priorities, handoff standards, and delivery quality to ensure continuity between applied AI prototyping and GCC-led build and operate.

Forward Deployed Engineering

Embed with business and scientific teams to scope, build, and deploy AI and agentic solutions from first prototype to stable production.

Own discovery, technical scoping, system design, and production rollout for priority deployments, working alongside BU IT and Platform Engineering.

Contribute hands-on to prototypes, integrations, and evaluations when progress or clarity depends on it.

Evaluate and onboard new AI model capabilities, including model upgrades, tool use, and MCP-based integrations, against quality, safety, and cost criteria.

Capture field feedback on where models and platforms succeed or fall short, and feed it into the roadmap and evaluation suites.

Codify repeatable patterns into reusable building blocks, playbooks, and reference architectures for adoption across business units.

This role might be for you if:

Bachelor's degree in related field required, Masters, MBA, or advanced degree preferred

10+ years of progressive experience in technical product management

Strong working knowledge of large language models (LLMs), foundation models, and modern generative AI, including their capabilities, limitations, and evaluation.

Familiarity with agentic AI: autonomous and multi-step agents, tool use, planning/orchestration, and human-in-the-loop design.

Hands-on understanding of emerging interoperability standards, including the Model Context Protocol (MCP) for connecting models to tools and data, and Agent-to-Agent (A2A) protocols for multi-agent coordination.

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 techniques.

Understanding of AI evaluation and observability: building evals, measuring quality/safety, monitoring drift, and managing model/agent performance in production.

Awareness of responsible and secure AI practices: guardrails, access controls, data privacy, and AI governance frameworks.

Familiarity with MLOps/LLMOps tooling and orchestration frameworks for building, deploying, and maintaining AI applications and pipelines.

Translates ambiguous business needs into clear product requirements and measurable outcomes.

Balances technical depth with product judgment and stakeholder empathy.

Keen eye for detail and thoughtful scrutiny of data before relying upon it.

Drives 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 in code when needed.

Scopes and delivers complex deployments in ambiguous, fast-moving environments, balancing scope, speed, and quality.

Comfortable owning roadmap, budget inputs, and outcomes for an assigned portfolio. Please copy and paste the desired job description for this role here. If you need a copy of an existing job description please reach out to TA or work with your HR Business Partner to develop one for a new role.

Does this sound like you? Apply now to take your first step towards living the Regeneron Way! We are committed to building a workplace with an inclusive culture. Regeneron is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion or belief (or lack thereof), sex, sexual orientation, gender identity or expression, gender reassignment, marital or civil partnership status, civil status, pregnancy or parental status, age, disability, nationality, citizenship status, ethnic or national origin, membership of the Traveler community, familial status, genetic information, military or veteran status, or any other characteristic protected under applicable law. Where required, we will provide reasonable accommodation to applicants with known disabilities or chronic illnesses during the recruitment process, unless such accommodation would impose undue hardship.

Where necessary, we disclose salary ranges for roles in all countries in which we operate. The final offer will be determined within the relevant range based on the country of employment, s