Mastercard currently has 16 active job listings related to artificial intelligence. The majority of these roles, 50%, are focused on serving infrastructure. Engineering is the primary function for these AI positions, with the United States being the top hiring country. Frequent technical tags include model serving, agent orchestration, and inference infrastructure, suggesting a focus on deploying and managing AI models. In the last 30 days, Mastercard has posted 23 new AI roles, representing a 667% increase from the previous 30-day period.
Currently tracking 3 active AI roles, down 63% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $156k–$265k (avg $211k).
Mastercard currently has 11 active AI-related roles in our index. The most common open titles are: Senior Software Engineer (3), Foundry R&D Software Engineer II, Lead Software Engineer, Lead Technical Program Manager, Manager, Software Engineering. Most positions are in Engineering.
Mastercard's active AI hiring is concentrated in: agents (45%), serving infrastructure (36%), application (18%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Mastercard is hiring AI talent in: United States (7 roles), Ireland (3 roles), Singapore (1 role).
Job postings at Mastercard most frequently reference: model serving, inference infra, agent orchestration, rag, guardrails.
In the past 30 days, Mastercard has posted 5 new AI-related roles. That is a -79% change versus the prior 30 days (24 → 5).
| Title | Stage | AI score |
|---|---|---|
| Foundry R&D Software Engineer II Software Engineer to join the Mastercard Foundry Research and Development team in Dublin. The role involves designing and implementing innovative capabilities using AI Tooling, working in an agile team, and researching alternative technical solutions. The team focuses on developing innovative products delivered at scale, shaping the future of commerce. | Agent | 5 |
| Lead Software Engineer Lead Software Engineer to drive the architecture, design, and development of a next-generation experimentation platform, incorporating Generative AI (GenAI) into software products and/or the software development lifecycle. Focus on building advanced, cloud-native services and modern frameworks on AWS/Azure, leveraging Databricks and Spark for data analytics and transformations. Role involves technical leadership, mentoring engineers, and ensuring high engineering standards for scalability, performance, security, and reliability. | Ship |
| 5 |
| Principal Software Engineer Mastercard is seeking a Principal Software Engineer to architect, build, and operate the API platform that securely exposes foundation model capabilities across the organization. This role is critical to enabling safe, scalable, and compliant adoption of generative AI and advanced analytics across Mastercard products and services. | ServeAgent | 5 |
| Principal Software Engineer - Architecture Principal Software Engineer (Architecture) to lead architecture for a service group in Mastercard's virtual card platform for Corporate Solutions. This role is pivotal in driving engineering excellence, scaling delivery capabilities, and fostering a culture of innovation, accountability, and continuous improvement. You will be responsible for aligning architecture and engineering strategy with business goals, mentoring high-performing teams, and ensuring the successful delivery of complex software solutions. | — | 0 |
| Lead Software Engineer Lead Software Engineer for Mastercard's Data & Services team, focusing on advanced analytics programs like Credit Risk, Portfolio Optimization, and Ad Insights. The role involves leading a team to design and build full-stack web applications and data pipelines, enhancing customer experience with new UIs, API-based data publishing, and scalable big data processes. The team works in a fast-paced, agile environment, contributing to the design, build, and testing of features, from intuitive UIs to backend data models and data flows. | — | 0 |