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Regeneron Pharmaceuticals

Develops biopharmaceutical therapies for serious diseases

Associate Director Product Management - Enterprise AI

Technical Product ManagementConfirmed live in the last 24 hours
Full-time$157.2k - $256.6k /yr

About the Job

Requirements

  • A bachelor's degree in a related field is required.
  • At least 10 years of progressive experience in technical product management is required.
  • Strong working knowledge of large language models, foundation models, and modern generative AI, including their 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 emerging interoperability standards, including the Model Context Protocol for connecting models to tools and data, and Agent-to-Agent protocols for multi-agent coordination.
  • Experience with retrieval-augmented generation, 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, including building evaluations, measuring quality and safety, monitoring drift, and managing model and agent performance in production.
  • Awareness of responsible and secure AI practices, including guardrails, access controls, data privacy, and AI governance frameworks.
  • Familiarity with MLOps and LLMOps tooling 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 scrutiny of data before relying on it.
  • Ability to drive 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.
  • Ability to own the roadmap, budget inputs, and outcomes for an assigned portfolio.

Responsibilities

  • Own the release strategy and roadmap for an assigned portfolio of the company's AI platforms and tools, aligned to the enterprise digital roadmap and platform strategy.
  • Build business cases to develop, acquire, or invest in new AI and machine learning capabilities, datasets, platforms, and tools.
  • Prioritize competing demands and frame recommendations with clear assumptions and analytical rigor.
  • Develop insight into 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, machine learning and AI models, and supporting tools, partnering with engineering and Business Digital teams to deliver products.
  • Define requirements for core platform capabilities, including data access, model serving, search and ranking, automation pipelines, and self-service tools.
  • Guide the use of AWS, Azure, and GCP to build and deploy automated machine learning and analytics pipelines.
  • Evaluate, pilot, and deploy new technologies against frameworks and criteria established with product leadership.
  • Drive product adoption by measuring usage, gathering feedback, and continuously improving products.
  • Partner with GCC engineering teams to translate platform architecture decisions and product requirements into scoped, production-ready deliverables; align on roadmap priorities, handoff standards, and delivery quality to ensure continuity between applied AI prototyping and GCC-led build and operations.
  • Embed with business and scientific teams to scope, build, and deploy AI and agentic solutions from initial 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 needed to make progress or provide clarity.
  • Evaluate and onboard AI model capabilities, including model upgrades, tool use, and Model Context Protocol-based integrations, against quality, safety, and cost criteria.
  • Capture feedback from deployments about where models and platforms succeed or fall short, and incorporate it into the roadmap and evaluation suites.
  • Codify repeatable patterns into reusable building blocks, playbooks, and reference architectures for adoption across business units.

Desired Qualifications

  • A master's degree, MBA, or advanced degree is preferred.

About the Company

Regeneron Pharmaceuticals

Develops biopharmaceutical therapies for serious diseases

Regeneron Pharmaceuticals develops and commercializes medicines for serious diseases, with a focus on cancer, eye diseases, allergic and inflammatory diseases, and infectious diseases. Its products come from using proprietary research capabilities and technologies to discover and develop therapies, often in collaboration with academic, research, and industry partners. Revenue comes from selling approved medicines and from licensing its technologies and entering co-development and co-commercialization partnerships. The company works with healthcare providers and regulators to ensure treatment delivery and safety. Its goal is to improve patient outcomes by bringing life-transforming medicines to market through rigorous R&D and strategic collaborations, maintaining leadership in biopharmaceutical innovation.

Company size
10,001+
Company stage
IPO
Headquarters
Town of Mount Pleasant, New York
Founded
1988

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