Join Mastercard Foundry, a dynamic research and development team focused on building innovative payment solutions at scale for global markets. This is a unique opportunity to work with cutting-edge technologies and shape the future of commerce. Our team thrives on innovation, from mining internal research to validating new product lines and engaging with startups.

We tackle diverse technological challenges across geographies, driving the development of advanced payment solutions. If you're passionate about creating novel solutions in a collaborative and fast-paced environment, this role is for you. Contribute to a team that values quality, best practices, and continuous learning.

Lead the analysis, design, and development of high-performance Java-based solutions. Contribute to defining requirements for new applications and customizations, ensuring adherence to development standards and best practices. Oversee the quality of application codebases and align them with enterprise development standards. Coach and develop junior engineers, applying advanced technical capabilities. Design complex applications, interfaces, and integrations, including enterprise-level integration with third-party middleware and custom solutions.

Take ownership of performance engineering for the enterprise software architecture. Provide functional guidance and training to other application developers. Engage in software development, code reviews, and daily support duties. Communicate domain-level directions through group-wide and external public speaking. Research and evaluate tools to meet domain-specific needs, ensuring robust and scalable software delivery.

Proficiency in modern software engineering concepts and methodologies is essential. Candidates should possess advanced knowledge of Java JDK 17 or greater, along with expertise in Tomcat, Spring, Spring Boot, and Shell Scripting. Experience with Docker, Kubernetes, or other container orchestration solutions is required. A strong understanding of automated unit testing frameworks like JUnit, CI/CD principles and tools (Jenkins, Gradle, Maven), and Source Control Management (Git) is crucial.

Familiarity with AI-assisted tools such as Claude Code, GitHub Copilot, and Codex for various development lifecycle stages is highly desired. Knowledge of agentic workflows, including multi-agent orchestration, tool integration, and responsible AI practices, is expected. Experience integrating AI workflows into Git-based development, CI/CD pipelines, and cloud-native deployments is a significant advantage. The ability to configure reusable AI workflows using specific frameworks is also a key requirement.