Backend Java Developer with 1+ year of experience building scalable cloud-based enterprise applications using Java, Spring Boot, and microservices architecture. Strong expertise in end-to-end product development, full SD…
Backend Java Developer with 1+ year of experience building scalable cloud-based enterprise applications using Java, Spring Boot, and microservices architecture. Strong expertise in end-to-end product development, full SDLC participation, OOP principles, design patterns, TDD practices, database optimization, and Agile collaboration across cross-functional teams.
Architected backend services for 5+ enterprise modules in Java & Spring Boot, owning the full lifecycle from low-level design through production deployment
Shipped 10+ RESTful APIs inside a microservices architecture, cutting average response latency by 15% through caching and query-level tuning
Slashed release cycle time by 30% by engineering Jenkins/Git/Maven/Artifactory pipelines that replaced manual deployment steps end-to-end
Eliminated 25+ production defects through systematic root-cause analysis, raising system stability by 18%
Wired Apache Kafka and RabbitMQ into 4+ services to handle 5,000+ messages per day, reducing synchronous coupling by 20%
Achieved 85%+ unit test coverage using TDD and design patterns (Singleton, Factory, MVC), shrinking regression defect rates by 20%
Optimized MySQL, MongoDB, and Redis queries — improved throughput and reduced latency across high-traffic endpoints
Containerized and orchestrated services with Docker and Kubernetes on AWS and Azure, supporting zero-downtime deployments
Completed 10+ Agile sprints with 100% on-time delivery; contributed to design reviews and mentored peers through code walkthroughs
Architected backend services for 5+ enterprise modules in Java & Spring Boot, owning the full lifecycle from low-level design through production deployment, Shipped 10+ RESTful APIs inside a microservices architecture, cutting average response latency by 15% through caching and query-level tuning, Slashed release cycle time by 30% by engineering Jenkins/Git/Maven/Artifactory pipelines that replaced manual deployment steps end-to-end, Eliminated 25+ production defects through systematic root-cause analysis, raising system stability by 18%, Wired Apache Kafka and RabbitMQ into 4+ services to handle 5,000+ messages per day, reducing synchronous coupling by 20%, Achieved 85%+ unit test coverage using TDD and design patterns (Singleton, Factory, MVC), shrinking regression defect rates by 20%, Optimized MySQL, MongoDB, and Redis queries — improved throughput and reduced latency across high-traffic endpoints, Containerized and orchestrated services with Docker and Kubernetes on AWS and Azure, supporting zero-downtime deployments, Completed 10+ Agile sprints with 100% on-time delivery; contributed to design reviews and mentored peers through code walkthroughs
Owned end-to-end technical design and development of backend services across 5+ enterprise modules using Java and Spring Boot, participating in complete SDLC from unit-level design through coding, unit testing, integration testing, and deployment, Delivered 10+ RESTful APIs within microservices architecture, improving response performance by 15% through optimization and adherence to architectural patterns, Collaborated with cross-functional teams in Agile/SCRUM environment across 10+ sprint cycles, participating in design discussions, code reviews, and achieving 100% on-time task completion, Resolved 25+ production defects through root-cause analysis and debugging, improving system stability by 18%, Automated CI/CD workflows using Jenkins, Git, Maven, and Artifactory, reducing release cycle time by 30% through pipeline optimization, Implemented Kafka and RabbitMQ for asynchronous communication across 4+ services, processing 5,000+ messages daily and reducing synchronous dependency by 20%, Applied OOP principles, design patterns (Singleton, Factory, MVC), and TDD practices achieving 85%+ unit test coverage and reducing regression defects by 20%, Optimized MySQL, MongoDB, and Redis queries improving database performance and throughput, Supported containerized deployments using Docker and Kubernetes in AWS/Azure cloud environments, Utilized JIRA for agile workflow management and executed Linux shell commands for deployment automation
Designed and developed an autonomous AI workflow automation system using Python and LLM APIs that can plan and execute multi-step tasks without manual intervention. Implemented prompt engineering techniques and structured output parsing to improve reliability and reduce hallucinations in AI responses. The system was tested across different workflows to improve accuracy and decision-making. This project helped strengthen my understanding of AI agents, automation pipelines, and backend system integration.
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