SOFTWARE ENGINEER • DISTRIBUTED SYSTEMS • CLOUD • GENAI
I architect low-latency backend platforms, event-driven systems, and AI-powered products that stay reliable under real production load.
I'm Vamshi Reddy Sappati, a Software Engineer focused on high-throughput backend systems, cloud-native platforms, and production AI. My work spans real-time order workflows, event-driven architectures, database optimization, and Retrieval-Augmented Generation systems built with Java, Python, Kafka, AWS, Kubernetes, LangChain, Pinecone, and OpenAI APIs.
The through-line is simple: reduce latency, remove operational friction, and build systems that remain understandable and dependable as traffic and complexity grow.
Selected projects designed around throughput, latency, retrieval quality, resilience, and deployability—not demo-only features.
LOW-LATENCY DISTRIBUTED EVENT STREAMING PLATFORM
Real-time event ingestion platform built with Spring Boot and Apache Kafka, engineered to process high-volume streams while keeping read paths fast with Redis and containerized orchestration.
ENTERPRISE KNOWLEDGE & RAG ENGINE
Enterprise retrieval platform combining vector search, LLM orchestration, and streaming responses to make large document collections searchable through natural-language queries.
HIGH-VOLUME ORDER & DELIVERY WORKFLOWS
Low-latency Java services with asynchronous event synchronization, optimized relational and NoSQL storage layers, caching, and production-grade API security for peak traffic.
REAL-TIME INVENTORY & IOT TRACKING
Backend services ingesting factory-floor telemetry across manufacturing facilities, with scalable NoSQL persistence and real-time dashboards for operations visibility.
Production backend engineering across microservices, REST, gRPC, authentication, concurrency, and service-to-service communication.
Event streaming, caching, durable persistence, and database design for systems that must remain responsive under concurrent load.
Containerized delivery and infrastructure automation across cloud environments, with reliable deployment workflows and observability.
Production AI integrations combining retrieval, vector databases, LLM APIs, streaming responses, and application-level orchestration.
Architecting low-latency Java/Spring Boot services, event-driven order workflows, database performance improvements, RAG-powered semantic search, LLM-assisted support services, and cloud-native CI/CD delivery.
Built inventory and IoT tracking services, modernized legacy J2EE workflows into REST APIs, created production dashboards, automated technical document search, and standardized cloud delivery with Docker, Jenkins, Azure, and Terraform.
Graduate education in computer science supporting advanced software engineering, systems design, and applied computing work.