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Abhilash Puttaram

@abhilashputtaram

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Senior Software Engineer | 8.5+ YOE | Java, Spring Boot, Microservices, Kafka, AWS | Distributed Systems

India

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What I'm looking for

I am seeking backend-focused roles where I can contribute to the scalable application development, performance improvements, work with microservices and cloud-native technologies, and drive secure, scalable production systems.

Senior Software Engineer with 8.5+ years of deep specialization in designing and building scalable, high-performance distributed systems using Java, Spring Boot, and Microservices architecture.

Expertise in event-driven systems using Apache Kafka, cloud-native development with AWS and Kubernetes and modernizing legacy applications into resilient cloud ready ecosystems.

Demonstrated success in delivering high-throughput, low-latency applications with performance improvement through optimization techniques.

Passionate about clean code, architectural excellence, and leveraging modern engineering practices including CI/CD, observability, and AI-assisted development tools to enhance productivity and accelerate high-quality delivery.

Experience

Work history, roles, and key accomplishments

Current

Lead Software Engineer

Current

UST Global Inc

Jan 2025 - Present (1 year 5 months)

Designed distributed microservices with Java, Spring Boot, and Kafka for data sync. Boosted performance by 70% via multithreading, caching, batch processing, and DB tuning. Resolved security issues, leveraged GitHub Copilot for productivity, and handled production support while enhancing observability with OpenObserve.

Java Spring Boot Microservices SQL NoSQL Apache Kafka GraphQL Docker Kubernetes AWS Redis

Technical Lead / Solution Architect

Xmplar Management Solutions Pvt Ltd

Sep 2017 - Jan 2025 (7 years 4 months)

Designed and implemented the migration of a monolithic application to a microservices architecture, significantly improving scalability and system flexibility.

Built Kafka-based event-driven systems, replacing RabbitMQ. Improved performance by 60% with Redis, async processing, and DB tuning. Achieved 50–200ms latency, led 30+ AWS zero-downtime releases.