Senior Software Engineer

Mastercard is a global payments technology company that supports secure, simple, smart, and accessible digital payments. The Senior Software Engineer will build scalable intelligent and agentic applications, AI-enabled engineering platforms, and reusable developer capabilities while improving software delivery productivity, reliability, security, and governance.

Responsibilities:

• Design, build, and evolve intelligent, agentic applications and platform capabilities that solve meaningful business problems at scale
• 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
• Partner with product, data science, and engineering teams to translate ideas into production-grade solutions with clear business impact
• Drive technical innovation by evaluating emerging tools, frameworks, and engineering practices, and identifying where they can create differentiated value
• Build reusable frameworks, services, and internal developer capabilities that improve developer experience and reduce delivery friction across teams
• Lead by example through hands-on engineering, sound technical judgment, and a strong bias for execution and ownership
• Solve complex technical problems with creativity, analytical rigor, and a pragmatic approach to trade-offs and delivery
• Improve software development lifecycle efficiency through automation, AI-assisted workflows, and engineering excellence
• Ensure AI-enabled systems are production-ready, observable, secure, governable, and resilient in enterprise environments
• Influence architecture, engineering standards, and best practices for building scalable modern applications in cloud-native ecosystems
• Continuously learn, experiment, and help elevate team capability in emerging AI and software engineering techniques
• 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

Requirements:

• 7+ years of strong software engineering experience building scalable, maintainable, production-grade systems
• Hands-on experience building applications or platforms using Generative AI, LLMs, or agentic design patterns
• Strong understanding of agent orchestration, tool use, prompt and context management, memory patterns, evaluation, and AI system design trade-offs
• Experience taking AI-enabled solutions from prototype to production with sound engineering discipline across reliability, observability, latency, cost, security, and governance
• Practical experience using AI coding and engineering assistants to improve productivity across the software development lifecycle
• Experience improving PDLC and SDLC efficiency through automation, CI/CD, automated testing, and AI-assisted engineering workflows
• Strong programming skills in one or more backend languages such as Java or Python, with the ability to write high-quality, well-tested, production-ready code
• Experience building services in cloud-native environments using Kubernetes and managed cloud services on AWS, Azure, or GCP
• Good understanding of APIs, distributed systems, event-driven architectures, data pipelines, and enterprise integration patterns
• Experience with modern AI frameworks, SDKs, and tools for building AI applications, agent workflows, and developer productivity solutions
• Strong problem-solving and analytical skills, with the ability to break down ambiguity and turn ideas into practical, scalable solutions
• Demonstrated innovative mindset with curiosity to learn new technologies, evaluate emerging tools, and apply them where they create value
• Strong sense of ownership and accountability, with the ability to independently drive initiatives from concept to delivery
• Excellent collaboration and communication skills, with experience working across engineering, product, AI, and business stakeholders
• Experience with modern front-end frameworks such as React and/or Next.js is beneficial
• Familiarity with inference APIs, embeddings, retrieval-augmented generation, model evaluation, and AI safety controls is preferred