Vice President, Product – AI Center of Excellence

About the role

Mastercard is looking for a Vice President to lead product strategy and execution for its enterprise AI platform, including the Agent Factory control plane and related AI capabilities. The role will shape the vision, roadmap, and operating model that enable internal teams to design, build, evaluate, deploy, monitor and scale trusted AI agents across the organization.

Key responsibilities

• Define and own a multi‑year product strategy for the Agent Factory and broader AI platform.
• Create and maintain a product roadmap covering experimentation, agent build, certification, deployment, monitoring and commercialization.
• Partner with engineering, architecture, data, security, legal, compliance, risk and business teams to align AI platform priorities with enterprise strategy.
• Translate emerging AI capabilities such as LLMs, agents, RAG, tool use, memory, evaluation harnesses and multi‑agent orchestration into practical enterprise product features.
• Own the Agent Factory control plane, including agent registry, lifecycle management, intake and approval workflows, risk tiering, model gateway, prompt and tool registries, evaluation and certification workflows, deployment governance, observability, audit evidence and FinOps.
• Prioritize platform investments based on business value, reuse potential, technical feasibility, risk, cost and adoption.

Required profile

• Extensive experience building enterprise or developer platforms, AI/ML products, data platforms or cloud‑native infrastructure in regulated or highly governed environments.
• Proven ability to operate at the intersection of product strategy, technical architecture, data governance, risk management and commercial value creation.
• Strong leadership skills with experience managing product managers and technical product managers.
• Track record of delivering safe, reusable, observable and production‑ready AI solutions.

Required skills

• Large Language Models (LLMs)
• Retrieval Augmented Generation (RAG)
• AI agent lifecycle management
• Cloud‑native infrastructure
• Data governance frameworks
• FinOps and value measurement