Mastercard is a global technology leader in the payments industry, dedicated to powering economies and empowering individuals across over 200 countries. We strive to build an inclusive digital economy that is secure, simple, smart, and accessible for everyone. Our team focuses on innovation and the development of new products using emerging technologies, managing them from inception through to market validation. Join us to shape the future of commerce globally.

This role is within the Mastercard Foundry Research and Development team, working on exciting, innovative products for global markets. The team is built on a strong foundation of research and development, exploring new product lines and collaborating strategically with startups to advance commerce solutions.

As a Lead Software Development Engineer, you will be instrumental in developing high-performance Java-based solutions. Your responsibilities will include:

- Analyzing, designing, and developing software solutions. - Contributing to application requirements and customizations, ensuring adherence to standards and best practices. - Maintaining the quality of application codebases and aligning with development standards. - Mentoring and developing junior engineers through technical guidance. - Designing complex applications, interfaces, and enterprise-level integrations. - Performing performance engineering and providing functional guidance and training. - Engaging in software development, code reviews, and day-to-day support. - Communicating domain-level directions effectively. - Researching and evaluating tools to meet domain-specific needs.

We are seeking a talented Lead Software Engineer with:

- Hands-on experience with AI-assisted tools such as Claude Code, GitHub Copilot, and Codex for various stages of the development lifecycle (analysis, design, code generation, review, documentation, testing, troubleshooting). - Ability to configure reusable AI workflows using AGENTS.md, custom skills, sub-agents, prompt patterns, context management, and project-specific instructions. - Knowledge of agentic workflows, including multi-agent orchestration, tool integration, human-in-the-loop controls, LLM evaluation, guardrails, and responsible AI practices. - Proficiency in validating AI-generated outputs for correctness, security, quality, maintainability, compliance, and production readiness. - Experience integrating AI workflows into Git-based development, automated quality gates, CI/CD pipelines, observability, and cloud-native deployment. - Proficiency with Java JDK 17 or greater, Tomcat, Spring, Spring Boot, Shell Scripting, and JSON. - Experience with container orchestration solutions like Docker and Kubernetes. - Expertise in Junit or other automated unit testing frameworks. - Knowledge of CI/CD principles and tools (Jenkins, Gradle, Maven). - Familiarity with Source Control Management and multi-developer code environments. - A degree in a relevant field and a strong foundation in modern software engineering concepts.