Java Lead/Architect - Agentic AI (Pune)

Lead Java Engineer (Architect) Java AI Experience - 10+ years Locaiton - Pune (hybrid) About the Role : We are seeking a Lead Software Engineer to design, build, and evolve high-throughput, low-latency, cloud-native platforms at Mastercard. This role requires deep hands-on engineering expertise, strong architectural judgment, and the ability to prototype, experiment, and productionize modern solutions across AWS, Kubernetes (EKS), Java microservices, and Agentic AI. You will operate as a technical owner, driving solution design end-to-end, mentoring engineers, and setting engineering standards while remaining deeply hands-on with code, infrastructure, and automation. Key Responsibilities : Architecture and Solution Design - Lead the architecture and design of distributed, low-latency, high-throughput systems running on AWS and EKS. - Design Java-based microservices platforms optimized for performance, scalability, resiliency, and operational excellence. - Make architectural decisions and trade-offs across compute, networking, data, and observability layers while meeting defined SLAs and SLOs. - Own non-functional requirements such as latency, throughput, availability, security, and cost efficiency. Hands-on Engineering and Prototyping - Develop production-grade Java applications using Spring Boot, gRPC, and REST APIs. - Build proof-of-concepts, prototypes, and technology experiments to validate architectural decisions. - Troubleshoot complex production issues across application, platform, and cloud environments. - Lead by example through active coding, development, and technical problem-solving. Cloud and Kubernetes (AWS / EKS) - Design and implement cloud-native solutions on AWS, including EKS, EC2, ALB/NLB, IAM, VPC, and Auto Scaling services. - Establish observability practices using logging, monitoring, metrics, and distributed tracing. - Define and implement Kubernetes-native patterns such as Horizontal Pod Autoscaling (HPA), resilient pod design, multi-AZ deployment strategies, and zero-downtime rollouts. - Build secure, scalable, and cost-effective cloud architectures. Agentic AI and Generative AI Enablement - Design and develop solutions leveraging Agentic AI and Generative AI technologies. - Utilize tools such as GitHub Copilot and custom AI agents to: - Improve developer productivity - Assist with code generation, refactoring, code reviews, and automated testing - Enable AI-driven workflows throughout the software development lifecycle, from design and development to testing and deployment - Ensure responsible, secure, and governed usage of AI technologies within engineering systems. CI/CD and Engineering Excellence - Design and maintain CI/CD pipelines that support: - Automated builds and testing - Security and compliance scanning - Continuous deployment and release automation - Infrastructure-as-Code and environment provisioning - Define and enforce engineering standards, best practices, and quality controls. - Conduct in-depth code reviews and architecture reviews. - Mentor engineers in cloud-native development, performance optimization, and up-to-date engineering practices. Required Qualifications Core Technical Skills - 10+ years of hands-on software engineering experience. - Strong expertise in Java and microservices architecture. - Proven experience building high-throughput, low-latency distributed systems. - Extensive AWS experience, including multiple production deployments on EKS. - Deep understanding of - Distributed systems - Concurrency and multithreading - Performance tuning and scalability - Resiliency and fault-tolerant architectures Cloud and Platform Engineering - Strong hands-on experience with Kubernetes (EKS) in production environments. - Deep knowledge of AWS networking, security, and scaling patterns. - Experience designing cloud-native, event-driven, and service-oriented platforms. AI and Modern Engineering - Experience applying Generative AI and Agentic AI in software engineering workflows. - Hands-on experience with GitHub Copilot or similar AI-assisted development tools. - Experience integrating AI capabilities into developer platforms and engineering processes is preferred. Engineering Leadership - Demonstrated ability to own architecture and technical execution from conception to production. - Proven experience mentoring engineers and guiding technical direction. - Strong communication and stakeholder-management skills, with the ability to clearly explain complex technical decisions. Preferred Qualifications - Experience in payments, fintech, or high-volume transaction processing systems. - Hands-on experience with gRPC, asynchronous messaging, or event-streaming platforms. - Knowledge of observability, reliability engineering, and SRE practices. - Experience modernizing legacy applications into cloud-native architectures. What Success Looks Like - Designs are simple, scalable, maintainable, and measurable. Le