
Abhijit Mishra
Backend Engineer and AI App Developer
Competenze

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Esperienza lavorativa
Software Engineer
Confidential • Full time
Jan 2026 - Present • 9 mos
Backend engineer at a fast-growing Indian startup. The company name is kept private. - Build and scale a location management system used across the product. - Work on the main website search engine to return fast and relevant results. - Build REST APIs and backend-for-frontend (BFF) services for many client apps. - Own MongoDB data modelling, query speed, deployments and high availability (PM2). - Track latency and errors with Elastic APM and Kibana. - Use Claude Code with custom MCP servers, skills and team rules to ship faster and safer. Tech: Node.js, Express.js, MongoDB (Mongoose), Elasticsearch, Kibana / Elastic APM, PM2, REST APIs, Claude Code.
Reliance Jio Infocomm
Full time • 1 yr 11 mos
Software Engineer
May 2024 - Nov 2025 • 1 yr 6 mos
Backend engineer at Jio Platforms for the JioPC and JioBusiness Cloud products. - Lead developer for JioPC, built on microservices. It handles 10,000+ transactions per month for customer onboarding and subscriptions. - Led JioBusiness Cloud development and mentored 2 developers. Delivered full flows: login, payments, autopay and invoicing. - Built 15+ Spring Boot microservices in Java 17. - Rebuilt the support ticket module with the Observer pattern, so new ticket types need no code changes. - Moved configuration to Apache Zookeeper: 35% fewer configuration failures in production. - Added Redis caching and session management: 45% faster responses. - Refactored a legacy service with SOLID principles: 30% less code complexity, 90%+ unit test coverage (JUnit 5, Mockito), 25% fewer production bugs. - Added structured logs across services: 35% less time spent debugging production issues. Tech: Java 17, Spring Boot, Microservices, Redis, MySQL, Apache Zookeeper, Docker, Kubernetes, OpenShift, Azure DevOps, JUnit 5, Mockito.
Data Engineering Intern
May 2023 - Oct 2023 • 5 mos
Data engineering internship at Jio Platforms. - Built Apache NiFi data pipelines (20+ processors) that read streaming data from Kafka topics, transform it and route it. These pipelines power real-time analytics on 10+ million records per day. - Tuned Hive (HQL) queries with partitioning and bucketing. Queries over terabytes of data ran 40% faster. Tech: Apache Kafka, Apache NiFi, Apache Hive, Apache Spark, Hadoop, Scala, HQL.