Bhandavya B V

Developed 12+ Java 17 and Spring Boot microservices integrated with React frontends for an AI-powered healthcare claims platform, reducing manual claims processing effort by 90%. Built Python prediction services with FastAPI and Pydantic alongside Java backends using asyncio and CompletableFuture to support concurrent processing. Integrated Azure AI Document Intelligence (via Python scripts and Java SDKs) to extract key-value pairs and tables from claims/receipts/supporting documents, reducing turnaround from hours to minutes. Implemented secure REST endpoints using Spring Security, OAuth 2.0, and JWT, with centralized exception handling and transaction management. Built persistence layers using Spring Data JPA and Hibernate, and deployed containerized microservices to Azure Kubernetes Service (AKS) using Docker, Terraform, and Azure DevOps pipelines, reducing release cycles from days to hours. Improved engineering velocity by integrating GitHub Copilot and Claude Code into debugging,

Developed 12+ Java 17 and Spring Boot microservices integrated with React frontends for an AI-powered healthcare claims platform, cutting manual claims processing effort by ~90%. Built Python prediction services using FastAPI and Pydantic alongside Java backends using asyncio and CompletableFuture for concurrent workflow execution. Integrated Azure AI Document Intelligence via Python scripts and Java SDKs to extract key-value pairs and tables from claims/receipts/supporting documents, reducing turnaround time from hours to minutes. Implemented secure REST endpoints with Spring Security, OAuth2, and JWT, using centralized exception handling and transaction management. Built persistence layers with Spring Data JPA and Hibernate and deployed containerized microservices to Azure Kubernetes Service (AKS) using Docker, Terraform, and Azure DevOps pipelines to reduce release cycles. Improved engineering workflows by contributing to GitHub Copilot and Claude Code usage in debugging, unit testi

Developed and integrated Java 17 and Spring Boot microservices with React front ends for an AI-powered healthcare claims platform, cutting manual claims processing effort by 90%. Built Python prediction services using FastAPI and Pydantic alongside Java back-end services with asyncio and CompletableFuture. Integrated Azure AI Document Intelligence to extract key-value pairs and tables from claims/receipts/supporting documents, reducing turnaround from hours to minutes. Implemented secure REST endpoints using Spring Security with OAuth2.0 and JWT, including centralized exception handling and transaction management. Built persistence layers with Spring Data JPA and Hibernate, deploying containerized microservices to Azure Kubernetes Service (AKS) using Docker, Terraform, and Azure DevOps pipelines to reduce release cycles from days to hours. Improved sprint velocity by ~25% using GitHub Copilot and Claude Code across debugging, unit testing, and implementation workflows.