Lead Software Development Engineer

Lead Software Development EngineerThe 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.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.