Director Product Management — Enterprise AI Platforms & Tools

About the role

The Director Product Management – Enterprise AI Platforms & Tools will set AI platform strategy and roadmap for the platforms and tools that put AI into the hands of colleagues across the organization.

Responsibilities

• Set AI platform strategy and roadmap for the platforms and tools that put AI into the hands of colleagues across the organization.
• 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.
• Lead the technical product development 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.
• Set the evaluation framework and criteria, pilot, and deploy new technologies as appropriate, 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.

Requirements

• Bachelor's degree in related field required, Masters, MBA, or advanced degree preferred
• 12+ 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
• 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
• Familiarity with retrieval-augmented generation (RAG), vector databases, embeddings, and grounding models in enterprise data
• Experience 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

Qualifications

• None specified

Skills

• Strong communication and leadership skills
• Ability to prioritize and manage multiple projects simultaneously
• Experience with agile methodologies and project management tools
• Knowledge of data science and machine learning concepts
• Experience with cloud computing platforms (AWS, Azure, GCP)
• Experience with software development and testing

Benefits

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

Pay

$183,100.00 - $305,200.00 annually

Schedule

Tarrytown, NY, 4+ times a week