Senior Director, Product Management – Enterprise AI Platforms & Tools

Regeneron

. Set AI platform strategy and roadmap for platforms and tools across the enterprise .

Posted 10/6/2026full-timeUnited StatesSenior💰 $216,100 - $360,200 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in AI platform strategy, technical product management, and the development of large-scale AI and machine learning models. Proficient in translating business needs into actionable product requirements while ensuring adherence to responsible AI practices and governance frameworks.

Highest-signal resume keywords

AI Platform StrategyTechnical Product ManagementLarge Language Models (LLMs)MLOps/LLMOps ToolingData Privacy and AI Governance

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Machine Learning/AI ModelsModel Context Protocol (MCP)Retrieval-Augmented Generation (RAG)Prompt EngineeringContext EngineeringFine-TuningModel CustomizationAI Evaluation and ObservabilityAutomation PipelinesData Access Requirements

Soft Skills

Stakeholder EmpathyAttention to DetailConsensus BuildingAnalytical RigorProduct Judgment

Tools & Technologies

AWSAzureGCPVector DatabasesAutomation ToolsOrchestration Frameworks

Certifications & Qualifications

Bachelor's DegreeMaster's Degree or MBA Preferred

Industry Keywords

Generative AIAgentic AIHuman-in-the-Loop DesignData PrivacyAI Governance Frameworks

Tech Stack

Tools & technologies

AWSAzureGoogle Cloud Platform

About the role

Key responsibilities & impact

Set AI platform strategy and roadmap for platforms and tools across the enterprise
Own the release strategy and roadmap aligned to the enterprise digital roadmap
Build business cases for developing, acquiring, or investing in AI/ML capabilities, datasets, platforms, and tools
Prioritize competing demands using clear assumptions and analytical rigor
Identify high-value opportunities to improve colleague and end-user experience
Define requirements for data access, model serving, search/ranking, automation pipelines, and self-serve tools
Lead technical product development of large-scale AI platforms, machine learning/AI models, and supporting tooling
Partner with engineering and Business Digital teams to deliver high-quality products
Guide use of AWS, Azure, and GCP for automated ML and analytics pipelines
Establish evaluation frameworks and criteria; pilot and deploy new technologies
Drive product adoption by measuring usage, gathering feedback, and continuously improving
Partner with GCC engineering teams to translate architecture decisions and product requirements into production-ready deliverables
Maintain alignment on roadmap priorities, handoff standards, and delivery quality between AI prototyping and GCC-led build and operations

Requirements

What you’ll need

Bachelor's degree in related field required
Master's, MBA, or advanced degree preferred
15+ years of progressive experience in technical product management
Strong working knowledge of large language models (LLMs), foundation models, and modern generative AI, including capabilities, limitations, and evaluation
Familiarity with agentic AI, including autonomous and multi-step agents, tool use, planning/orchestration, and human-in-the-loop design
Hands-on understanding of 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 evals, quality/safety measurement, drift monitoring, and model/agent performance management in production
Awareness of responsible and secure AI practices, including guardrails, access controls, data privacy, and AI governance frameworks
Familiarity with MLOps/LLMOps tooling and orchestration frameworks
Ability to translate ambiguous business needs into clear product requirements and measurable outcomes
Ability to balance technical depth with product judgment and stakeholder empathy
Keen attention to detail and thoughtful scrutiny of data
Ability to drive consensus across engineering, data science, business, IT, and Legal
Comfort owning roadmap, budget, and outcomes end-to-end

Benefits

Comp & perks

Annual bonuses or other incentive plans
Equity awards
Pension or retirement benefits
401(k) company match
Health and wellness programs
Fitness centers
Medical, dental, vision, life, and disability insurance benefits
Paid time off
Family support benefits
Reasonable accommodation during the recruitment process where required