Lead Software Development Engineer

Overview The Lead Software Development Engineer is a technical leader responsible for driving software architecture, engineering strategy, and delivery of Mastercard's next-generation payment platforms. This role combines hands-on engineering leadership with architecture ownership, modernization initiatives, and adoption of Agentic AI-powered engineering practices.

What You Will Do Software Architecture & Engineering Leadership - Lead software design and architecture decisions across multiple teams and platforms. - Define engineering standards for software development, testing, security, operability, and deployment. - Conduct architecture reviews and provide technical governance across projects. - Mentor engineers and cultivate a culture of engineering excellence.

Scalable Distributed Systems - Architect highly available, fault-tolerant distributed systems capable of processing millions of transactions daily. - Drive performance engineering initiatives including load testing, capacity planning, scalability analysis, and production optimization. - Design solutions supporting low latency, high throughput, resiliency, and operational excellence.

Event-Driven Architecture - Design and implement large-scale event-driven architectures utilizing Kafka and modern messaging patterns. - Drive adoption of asynchronous processing and distributed system design best practices.

Cloud Native Engineering - Lead development and deployment using PCF, Kubernetes, Docker, and CI/CD platforms. - Champion platform engineering and infrastructure automation practices.

Security, Reliability & Operations - Establish secure coding standards and application security best practices. - Drive operational readiness, observability, monitoring, and supportability strategies. - Lead complex troubleshooting efforts, root cause analysis, and remediation activities. - Establish standards for unit, functional, and integration testing.

Agentic AI Engineering - Lead adoption of AI-assisted development, AI agents, MCP-based integrations, autonomous workflows, and modern engineering productivity tools. - Evaluate and implement emerging AI engineering capabilities while ensuring governance and responsible AI practices.

All About You - 10+ years of software engineering experience. - 3+ years leading large-scale distributed system initiatives. - Expert-level Java, Spring Boot, REST APIs, microservices architecture, and distributed systems expertise. - Strong software architecture and software design leadership experience. - Deep expertise in performance engineering and reliability engineering. - Extensive experience implementing secure coding standards and software quality practices. - Experience mentoring engineers and leading technical decision-making. - Deep understanding of observability, monitoring, operability, and production support. - Demonstrated experience with AI-assisted software development, AI agents, MCP, RAG, and agentic workflows. - Strong communication, stakeholder management, and technical leadership skills.