Vice President, Product - AI Center of Excellence
$245k - $391kMastercard
Vice President, Product - AI Center of Excellence
Role Overview
We are seeking a Vice President, AI Product Management to lead product strategy and execution for the company’s enterprise AI platform capabilities, including the Agent Factory control plane, agent development lifecycle, LLM enablement, evaluation frameworks, and governed AI build patterns.
This leader will own the product vision, roadmap, and operating model for enabling internal teams to design, build, evaluate, deploy, monitor, and scale trusted AI agents across the enterprise. The role will manage a small team of Product Managers and Product Managers-Technical responsible for the platform capabilities that make AI agent development safe, reusable, observable, and production-ready.
- Product Strategy & Roadmap
o Create a product roadmap that supports experimentation, agent build, certification, deployment, monitoring, and commercialization at scale.
o Partner with engineering, architecture, data, security, legal, compliance, risk, and business teams to align AI platform priorities to enterprise strategy.
o Translate emerging AI capabilities, including LLMs, agents, RAG, tool use, memory, evaluation harnesses, and multi-agent orchestration, into practical enterprise product capabilities.
o Prioritize platform investments based on business value, reuse potential, technical feasibility, risk, cost, and customer adoption.
- Agent Factory Control Plane Ownership
Agent registry
Agent lifecycle management
Intake and approval workflows
Risk tiering
Model gateway
Prompt registry
Tool registry
Evaluation and certification workflows
Agent deployment governance
Observability and audit evidence
FinOps and value measurement
o Ensure the control plane provides a consistent, governed path from agent idea to production deployment.
o Partner with engineering to ensure the control plane integrates with AWS, Databricks, PCF/on-prem environments, enterprise identity, access controls, data governance, and observability systems.
- AI Build & Agent Enablement
o Support platform capabilities such as:
Agent Studio / builder experience
Prompt playgrounds
Agent templates
LLM model access
RAG patterns
Tool-calling frameworks
Agent evaluation harnesses
Guardrails
Human-in-the-loop workflows
Runtime deployment patterns
Reusable agent components
o Establish standard patterns for building agents across data discovery, customer support, engineering productivity, fraud/risk, sales enablement, finance, operations, and internal knowledge workflows.
o Ensure product teams can safely experiment with agents in sandbox environments while maintaining a clear path to certified production deployment.
- Governance, Risk & Compliance
o Partner with legal, privacy, security, compliance, risk, and audit teams to define practical controls for production AI agents.
o Ensure every production agent has a named owner, risk classification, approved data sources, approved tools, evaluation evidence, telemetry, and a support model.
o Define approval gates and production-readiness criteria based on agent autonomy, data sensitivity, tool access, regulatory exposure, and business impact.
o Drive consistency across AI governance, model governance, data governance, and enterprise access-control policies.
- Customer Adoption & Commercialization
o Create product experiences, onboarding guides, documentation, templates, and enablement programs that make it easier for teams to build agents through the platform.
o Develop metrics to track usage, adoption, reuse, quality, cost, risk, and business value.
o Support the evolution of the Agent Factory from internal platform capability to commercializable AI product foundation.
o Partner with business and product teams to identify AI agent capabilities that can be embedded into customer-facing products, partner solutions, or monetizable services. Required Qualifications
- Experience owning enterprise-scale platforms, internal developer platforms, AI/ML platforms, data platforms, cloud platforms, workflow platforms, or governed technology products.
- Strong understanding of generative AI, LLMs, AI agents, RAG, prompt management, model evaluation, tool use, and enterprise AI risk considerations.
- Experience working in regulated, security-conscious, or highly governed environments such as financial services, payments, banking, insurance, healthcare, or large enterprise technology.
- Ability to translate complex technical capabilities into clear product strategy, roadmaps, executive narratives, and customer-facing value propositions.
- Strong executive communication skills with the ability to influence senior leaders across product, engineering, data, security, risk, compliance, legal, and business functions.
- Experience defining product metrics, OKRs, adoption goals, platform KPIs, and business value measures.
- Strong technical fluency with cloud, APIs, platform architecture, data governance, identity/access management, observability, and CI/CD concepts.
All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:
- Abide by Mastercard’s security policies and practices;
- Ensure the confidentiality and integrity of the information being accessed;
- Report any suspected information security violation or breach, and
- Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.
In line with Mastercard’s total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary and may be eligible for an annual bonus or commissions depending on the role. The base salary offered may vary depending on multiple factors, including but not limited to location, job-related knowledge, skills, and experience. Mastercard benefits for full time (and certain part time) employees generally include: insurance (including medical, prescription drug, dental, vision, disability, life insurance); flexible spending account and health savings account; paid leaves (including 16 weeks of new parent leave and up to 20 days of bereavement leave); 80 hours of Paid Sick and Safe Time, 25 days of vacation time and 5 personal days, pro-rated based on date of hire; 10 annual paid U.S. observed holidays; 401k with a best-in-class company match; deferred compensation for eligible roles; fitness reimbursement or on-site fitness facilities; eligibility for tuition reimbursement; and many more. Mastercard benefits for interns generally include: 56 hours of Paid Sick and Safe Time; jury duty leave; and on-site fitness facilities in some locations.
Pay RangesNew York City, New York: $245,000 - $391,000 USD
$245k - $391k
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