Software Engineer II

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 Software Engineer II Overview The CNPF Data & AI organization is looking for an exceptional Software Engineer II to help build the next generation of intelligent, agentic applications and engineering platforms. This is a high-impact role for a hands-on engineer who combines deep software engineering expertise with a passion for AI, innovation, and practical problem solving. You will design and build scalable, production-grade systems that leverage AI, agentic workflows, and modern developers tooling to accelerate product delivery and improve engineering productivity across the full product development lifecycle. You will work at the intersection of software engineering, AI capability development, developer experience, and platform innovation—turning emerging technologies into secure, reliable, and reusable capabilities that create measurable business value. Position Responsibilities As a Software Engineer II, you will: Software Design, Architecture & Development: • Design, build, and evolve intelligent, agentic applications and platform capabilities that solve meaningful business problems at scale • Apply robust software design principles, design patterns, and architectural best practices to create scalable, maintainable, and extensible systems • Influence and contribute to system architecture decisions, including distributed systems, event-driven patterns, and cloud-native design • Develop high-quality, well-structured, and efficient code leveraging strong data structures and algorithmic thinking AI-Enabled Engineering & Innovation: • Apply AI and agentic development patterns to improve engineering productivity across design, coding, testing, debugging, documentation, release engineering, and operational support • Use modern tools and coding assistants thoughtfully to accelerate delivery while maintaining strong standards for quality, security, reliability, and maintainability • Evaluate emerging AI tools, frameworks, and platforms and integrate them into engineering workflows where they create measurable value Testing & Quality Engineering: • Design and implement comprehensive testing strategies, including unit, functional, integration, and end-to-end testing • Build and maintain automated testing frameworks and integrate them into CI/CD pipelines • Ensure high levels of test coverage, system reliability, and defect prevention across the software lifecycle • Leverage AI-assisted solutions to enhance testing efficiency and effectiveness Code Quality & Engineering Excellence: • Conduct and actively participate in code reviews, ensuring adherence to coding standards, maintainability, security, and best practices • Champion engineering excellence, including clean code, reusable design, and continuous improvement practices • Mentor peers through review processes and knowledge sharing Performance, Security & Reliability: • Design and optimize systems for performance, scalability, latency, and cost efficiency • Apply and promote secure coding practices, integrating security considerations into all stages of development (DevSecOps) • Ensure systems are observable, resilient, and production-ready, with strong monitoring, alerting, and incident response capabilities Operability & Troubleshooting: • Build systems with strong operational readiness, ensuring maintainability and supportability in production environments • Diagnose and resolve complex technical issues across distributed systems, leveraging structured tr