Lead Software Development Engineer

Lead Software Development Engineer

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.

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.