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.
Lead Technical Product Manager
We are seeking a Lead Technical Product Manager to drive the definition, execution, and operationalisation of AI-powered products and services. This role will be responsible for managing AI rules, operational processes, platform capabilities, and product delivery while partnering with engineering, data science, business, risk, and operations teams. The ideal candidate combines strong product management expertise with technical depth in AI/ML systems, platform products, APIs, data services, and operational workflows. The individual will ensure AI solutions are scalable, reliable, measurable, and aligned with business objectives. This aligns with the responsibilities of Lead Product Manager-Technical roles found internally, including ownership of roadmap, backlog, feature prioritisation, delivery, and operational performance.
Responsibilities
Product Strategy & Roadmap
•Define product vision and roadmap for AI-powered capabilities and operational services.
•Partner with business stakeholders to identify opportunities for automation, intelligence, and operational improvements.
•Translate business needs into product requirements, features, and delivery plans.
•Prioritise investments based on customer value, operational efficiency, business impact, and technical feasibility.
•Define and manage AI business rules, decision criteria, thresholds, and exception handling processes.
•Work with data scientists and engineering teams to establish measurable success criteria for AI-driven capabilities.
•Drive continuous optimisation of AI outcomes through experimentation, monitoring, and operational feedback.
•Manage rule change processes and feature enhancements across AI products.
Product Ownership & Delivery
•Own backlog prioritisation, feature definition, and release planning.
•Develop epics, user stories, acceptance criteria, and success metrics.
•Lead agile ceremonies including backlog grooming, sprint planning, reviews, and release readiness.
•Partner with engineering teams to ensure predictable and high-quality delivery.
Technical Leadership
•Collaborate with architects and engineers on APIs, integrations, data flows, and platform capabilities.
•Evaluate trade-offs involving scalability, latency, resilience, security, and maintainability.
•Ensure technical solutions support long-term platform strategy and reuse.
•Drive platform thinking rather than one-off feature development.
Stakeholder Management
•Serve as the primary product owner for AI initiatives.
•Communicate roadmap priorities, risks, dependencies, and outcomes to leadership.
•Coordinate across Product, Engineering, Data Science, Operations, Business, and Customer Success teams.
•Influence strategic decisions using data and customer insights.
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.
Requirements
•8+ years in Product Management, Technical Product Management, or Product Owner roles.
•Experience delivering AI, Machine Learning, Analytics, Data, API, or Platform products.
•Experience working in Agile and SAFe delivery environments.
•Demonstrated success driving cross-functional initiatives from concept to production.
•Strong understanding of: AI and Machine Learning concepts, Generative AI and Agentic AI use cases, APIs and Microservices, Cloud Platforms, Data Engineering and Analytics, Platform Architecture, Operational Metrics and Monitoring, Agile and SAFe delivery methodologies.
