Headline

Java Backend Developer | 3+ Years | Spring Boot | Microservices | Kafka | Redis | AWS | AI/GenAI | Bedrock | RAG | Docker | REST APIs | CI/CD | MySQL | Hibernate | JPA | Telecom | Open to Work | Actively Looking |Jenkins

About

I build backend systems that handle real production traffic. Over the past 3 years at CGI, I’ve worked on telecom-grade platforms serving 1,200+ concurrent users — where slow APIs mean dropped customers and downtime means revenue loss. What I’ve delivered: → 30% faster API response times through Redis caching and query optimization → 40% reduction in database load via indexing and TTL-based cache invalidation → 50% faster batch processing using multithreaded pipelines → AI-powered code review agent using Amazon Bedrock and RAG pipelines — reduced review turnaround by 60% Beyond the numbers, I obsess over clean architecture, maintainable code, and systems that don’t break at 2AM. I’ve worked in high-pressure telecom environments where reliability isn’t optional — it’s the baseline. I’ve designed and built: → Event-driven microservices using Kafka with guaranteed message delivery and retry mechanisms → Distributed caching layers with Redis for high-read, low-latency workloads → Secure REST APIs with Spring Security and JWT authentication → ElasticSearch integrations for fast full-text search across millions of records → CI/CD pipelines using Jenkins and Docker for zero-downtime deployments → GenAI integrations using Amazon Bedrock, LLMs, and RAG for intelligent developer tooling → Multithreaded batch processors handling millions of records with optimized throughput My stack: Java 8/17 · Spring Boot · Spring Security · Microservices · Kafka · Redis · MySQL · PostgreSQL · AWS · Docker · Kubernetes · ElasticSearch · Hibernate · JPA · JUnit · Jenkins · Git · REST APIs · CI/CD · Amazon Bedrock · LLMs · RAG What drives me: I don’t just write code that works — I write code that scales. I care deeply about system design, concurrency, fault tolerance, and building platforms that teams are proud of. I’ve mentored junior developers, contributed to architecture decisions, and collaborated with product and QA teams to ship reliable features in agile sprints. I believe great backend engineering is invisible — systems just work, APIs are fast, and on-call nights are quiet. Currently exploring: → Senior Backend Engineer roles → Platform Engineer roles → Java/Spring Boot Developer positions → Backend roles in FinTech, HealthTech, or AI-first companies → Open to full-time, contract, and remote opportunities worldwide I’m actively upskilling in GenAI engineering — building LLM-powered backend tools, exploring vector databases, and integrating AI agents into production Java microservices architectures. shivanshupandey1808@gmail.com 15 days notice period

Location

Bengaluru

Work experience

Back End Developer at CGI, Jun 2023 - Present · 3 yrs 1 mo, Bengaluru, Karnataka, India, ▪ Engineered high-performance backend services for a Telecom Platform supporting 1,200+ concurrent users, improving API response times by 30% through query optimization and Redis caching strategies. ▪ Implemented Redis caching with TTL-based invalidation and optimized MySQL queries using indexing and execution plans, reducing database load by 40%. ▪ Developed and maintained microservices handling order lifecycle, billing, and provisioning workflows using Spring Boot, Hibernate, and Kafka for event-driven processing. ▪ Improved batch processing efficiency by 50% using ExecutorService thread pools and concurrent data pipelines. ▪ Implemented JWT-based authentication with role-based access control using Spring Security across backend services. ▪ Built an AI-powered code review agent using Amazon Bedrock (Claude/Titan) that analyzes pull requests, detects code smells, and generates fix suggestions — reducing code review turnaround by 60%. ▪ Designed RAG pipelines using vector embeddings and similarity search for contextual issue summaries from internal documentation. ▪ Monitored microservices health using AWS CloudWatch — set up custom metrics, alarms, and dashboards reducing incident response time by 45%. ▪ Deployed containerized Spring Boot services on AWS ECS using Docker and automated CI/CD pipelines via Jenkins, achieving zero-downtime releases. ▪ Integrated ElasticSearch for full-text search across millions of telecom records, reducing search query latency by 70% compared to traditional MySQL queries. ▪ Built LLM-powered internal documentation assistant using Amazon Bedrock and RAG, enabling engineers to query 500+ internal docs in natural language — cutting onboarding time by 35%. ▪ Designed dead letter queue (DLQ) strategies in Kafka to handle message failures gracefully, improving system fault tolerance and reducing data loss incidents to zero. ▪ Consistently delivering features on time with 95%+ test coverage using JUnit and Mockito.

Education

B.Tech, Computer Science, Bengal College of Engineering and Technology 125

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