Director, AI Product Definition & Execution

Mastercard•O'fallon, MO

1d•Onsite

About The Position

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. 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. 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.

Requirements

10+ years in product, engineering, or technical leadership
Strong engineering/architecture fluency
Experience designing operating models
Hands-on AI usage in workflows
Systems thinking and ability to scale quality
Engineering-grade rigor in product definition
AI-first mindset
Systems thinking
Leadership in ambiguity
Executive communication skills

Nice To Haves

Experience with large-scale platforms and APIs
Payments or regulated industry experience
Operating model transformation experience
Exposure and use of AI-driven tooling

Responsibilities

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.
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.
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 definition quality and AI models.
Evolve PMT from requirement writers to problem framers, system designers, and decision enablers.
Upskill PMTs in product thinking, systems thinking, and practical, responsible AI usage.
Establish shared standards, language, and expectations that scale PMT effectiveness across teams.
Own the AI enabled PMT functional maturity.
Partner closely with Product, Engineering, and Architecture leaders to align intent, feasibility, constraints, and sequencing.
Reduce ambiguity and friction at handoffs by improving the clarity and consistency of PMT outputs with AI-enabled decisioning.
Build trust through transparency, quality signals, and predictable operating mechanisms rather than individual interactions.

Benefits

insurance (including medical, prescription drug, dental, vision, disability, life insurance)
flexible spending account and health savings account
16 weeks of new parent leave
up to 20 days of bereavement leave
80 hours of Paid Sick and Safe Time
25 days of vacation time
5 personal days
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