Director, AI Product Definition & Execution

Our Purpose

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.

Title and Summary

Director, AI Product Definition & Execution

Who We Are

Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible.

Core Services powers Mastercard's foundational payment platforms, including Consumer Credit, Debit, Prepaid, Commercial, Integrated Processing Solutions, Enterprise Gateway Solutions (EGS), Account Level Management (ALM), MPGS, and Security Services.

Within Core Services, Product Management Technical (PMT) plays a critical role in translating product strategy and business intent into execution-ready work that engineering teams can reliably deliver. This role sits at the intersection of product, engineering, and architecture, and is central to evolving how we scale quality, clarity, and predictability across highly complex, regulated platforms.

Role Overview

We are seeking a director to redefine and modernize the Product Management Technical (PMT) operating model by applying an AI‑first lens to how product intent is shaped, refined, and delivered to engineering.

This is not a traditional product ownership or delivery leadership role. The leader will enter an existing operating model, observe and assess how PMT functions today, and identify systemic sources of ambiguity, rework, and execution of friction leveraging AI and PMT skills to resolve the same.

This leader will redesign how product ideas become buildable software by owning the operating model, the PMT practices, decision frameworks, and AI‑enabled workflows that drive clarity, speed, and predictability across our engineering organization.

Success will be measured not by artifact production, but by improved delivery outcomes-higher backlog readiness, reduced iteration churn, fewer clarification cycles, stronger engineering trust, and more predictable execution across platforms.

The Mission

Transform PMT from a documentation layer into a high-leverage, AI-enabled product definition engine that produces clear, testable, execution ready Features and Stories, reduces ambiguity, improves delivery outcomes, and scales quality through operating mechanisms and AI
- Driven Workflows not individual heroics.

Primary Accountabilities

1. Product Definition Operating Model

* Assess the current PMT operating model and identify gaps in clarity, ownership, and decision-making.

* Define and standardize decomposition patterns (Epics → Features → Stories) that align with how engineering builds and increments value.

* Establish and enforce a consistent Definition of Ready aligned with engineering.

* Standardize acceptance criteria, constraints, and non‑functional requirements across platforms.

2. AI-Enabled Product Definition System

* Design how AI is embedded directly into PMT workflows-not as an add‑on, but as a core product management capability.

* Use AI to support requirement synthesis, feature and story generation, acceptance criteria creation, and validation.

* Leverage Jira, Confluence, historical delivery data, platform documentation, and architectural signals as structured AI inputs.

* Define prompt frameworks, guardrails, and AI‑based quality scoring to ensure outputs meet PMT and engineering standards.

3. Quality System & Feedback Loops

* Define quality metrics owned by PMT, including story quality, readiness scores, and ambiguity indicators leading to PMT Maturity Matrix.

* Track downstream delivery signals such as defects, rework, iteration churn, and delivery delays.

* Build closed‑loop feedback mechanisms that continuously connect delivery outcomes back to product…