ARJUN YADAV

Served as Lead Technical Architect across backend microservices, real-time stream processing, and AI integrations supporting 10M+ daily transactions across ticketing, booking, and guest analytics. Architected an automated vulnerability remediation pipeline triggered daily via GitHub Actions and Azure DevOps, integrating FastAPI and LLM APIs to scan for CVEs, bump Maven dependencies, refactor breaking changes, run JUnit 5 tests, and open PRs. Led AI-assisted engineering adoption across 15+ engineers using Cline and GitHub Copilot, standardizing prompt libraries and improving delivery speed. Built and deployed RAG and agentic solutions using AWS Bedrock and Google Vertex AI integrated with Spring Boot microservices. Designed scalable Flink/Kafka stream processing with sub-second latency and optimized PySpark batch jobs on AWS EMR to reduce compute cost and runtime. Improved reliability and operational visibility using OpenTelemetry, Grafana, and Prometheus, reducing MTTR by 40%.

Decomposed a legacy Employee Management System monolith into domain-driven Spring Boot and Node.js microservices deployed on AWS EKS and Azure AKS. Developed secure REST APIs with Spring Boot and Express.js, including rate limiting, CORS policy enforcement, and SAML/OIDC authentication with payload encryption. Built internal React and Angular-based portals and dashboards consuming microservice endpoints. Architected integration pipelines using Apache Camel, Spring Integration, and Kafka to transform and dispatch messages across legacy systems. Implemented resilience and gateway patterns using Spring Cloud Gateway and Resilience4j; used Redis caching for high-volume/global lookups to reduce database load. Tuned PostgreSQL/MySQL performance and integrated DynamoDB/Cosmos DB for low-latency key-value access. Delivered CI/CD pipelines with Azure DevOps and Jenkins, including SonarQube quality gates, Docker, and Terraform.

Built customer-facing retail web applications using React/Redux and Java/Spring Boot microservices. Developed event-driven inventory reconciliation microservices using Kafka and ActiveMQ, writing to MongoDB, and implemented nightly reconciliation batch workloads with Apache Spark on AWS EMR processing data into Parquet on S3. Designed REST APIs with Spring Boot and Hibernate ORM with API semantic versioning, payload validation, and secure token authentication. Provisioned AWS infrastructure (EC2, S3, RDS, DynamoDB) via Terraform and deployed containerized services onto EKS to achieve 99.99% availability. Created Python automation scripts for scheduled ETL and supplier catalog validation, and used WebSockets for real-time inventory notifications and live stock updates. Authored unit/integration tests with JUnit 5 and Mockito and maintained strong code coverage using React Testing Library.