Senior Software Engineer
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.
Title and Summary
Senior Software EngineerOverview:We are looking for a highly skilled and motivated Senior Software Engineer to design, develop, and evolve scalable, reliable, secure, and high-performance applications across the frontend and backend.
The ideal candidate will have strong hands-on experience with Java, Spring Boot, REST APIs, gRPC, microservices, React, relational databases, messaging, CI/CD, and cloud-native technologies.
The role requires a strong balance of full-stack development, system design, problem solving, technical ownership, AI adoption, and collaboration. The engineer will work closely with product managers, architects, DevOps engineers, and other engineering teams to deliver high-quality solutions from conception through production.
Key Responsibilities:
- Design, develop, test, deploy, and maintain full-stack applications using Java/Spring Boot and React.
- Develop scalable and maintainable backend services using Java and Spring Boot.
- Design and implement REST APIs, gRPC services, microservices, and event-driven components.
- Develop responsive, reusable, and maintainable user interfaces using React, JavaScript/TypeScript, HTML, and CSS.
- Design appropriate communication patterns using REST, gRPC, and asynchronous messaging based on business and technical requirements.
- Own software development initiatives end-to-end, from requirements and technical design through implementation, testing, deployment, and production support.
- Participate in architecture and technical design discussions with a focus on scalability, performance, availability, security, and maintainability.
- Design efficient relational database models and develop optimized SQL queries.
- Develop integrations with messaging platforms such as Apache Kafka.
- Build and maintain automated unit, integration, API, contract, and end-to-end tests across frontend and backend components.
- Leverage AI-assisted development tools such as GitHub Copilot and other approved AI coding/productivity tools to improve development speed, code quality, testing, documentation, troubleshooting, and developer productivity.
- Identify and drive opportunities to use AI for engineering automation, including code generation, test generation, code analysis, documentation, refactoring, debugging, and developer workflows.
- Evaluate AI-generated code and recommendations critically, ensuring correctness, security, maintainability, performance, and compliance before adoption.
- Promote responsible adoption of AI tools while following organizational security, privacy, intellectual property, and engineering standards.
- Troubleshoot production issues, perform root-cause analysis, and implement sustainable corrective actions.
- Conduct code reviews and contribute to coding standards, design guidelines, and engineering best practices.
- Mentor junior and mid-level engineers and contribute to technical knowledge sharing.
- Collaborate effectively with cross-functional and distributed teams.
Backend
- Strong hands-on experience with Java 17/21+.
- Strong experience with Spring Framework / Spring Boot.
- Strong understanding of RESTful API design and microservices architecture.
- Hands-on experience with gRPC and Protocol Buffers (protobuf).
- Good understanding of gRPC concepts including service contracts, streaming, deadlines/timeouts, status codes, error handling, interceptors, and backward-compatible API evolution.
- Strong understanding of object-oriented design, SOLID principles, design patterns, and clean code practices.
- Experience with JPA/Hibernate and Spring Data.
- Strong experience with relational databases such as Oracle, PostgreSQL.
- Good understanding of SQL, database design, indexing, transactions, and query optimization.
- Experience with Apache Kafka or equivalent messaging/event-streaming technologies.
- Good understanding of multithreading, concurrency, caching, transactions, and performance optimization.
- Strong hands-on experience with React.
- Strong knowledge of JavaScript and/or TypeScript.
- Experience building responsive, reusable, component-based UI applications.
- Good understanding of React hooks, state management, component lifecycle, routing, and asynchronous API integration.
- Experience with frontend state-management solutions such as Redux, Context API, or equivalent.
- Strong understanding of HTML5, CSS3, responsive design, and browser fundamentals.
- Experience integrating frontend applications with REST and/or gRPC-backed services.
- Understanding of frontend performance optimization, accessibility, security, and browser compatibility.
- Strong practical experience with Test-Driven Development (TDD) and test-first development practices.
- Strong understanding of the Red-Green-Refactor development cycle.
- Experience writing effective unit, integration, API, contract, and end-to-end tests.
- Backend testing experience with JUnit 5, Mockito, Spring Boot Test, or equivalent frameworks.
- Frontend testing experience with Jest, React Testing Library, or equivalent frameworks.
- Experience with Playwright, or similar end-to-end testing frameworks.
- Ability to design testable code and identify appropriate testing boundaries across unit, integration, and E2E layers.
- Ability to incorporate automated tests into CI/CD pipelines and enforce quality gates.
- Practical experience using AI coding assistants and developer productivity tools such as GitHub Copilot, ChatGPT, or equivalent tools.
- Ability to effectively use AI for code generation, refactoring, test generation, debugging, documentation, code review, and technical analysis.
- Ability to write effective prompts and provide appropriate context to AI tools to achieve high-quality engineering outcomes.
- Ability to validate, review, and improve AI-generated code rather than relying on AI output without engineering judgment.
- Understanding of responsible AI adoption, including data privacy, security, intellectual property, confidentiality, and organizational AI usage policies.
- Willingness to continuously evaluate and adopt emerging AI-assisted engineering practices that improve developer productivity and software quality.Corporate Security Responsibility
- 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.