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Nikshitha Aella
Mid-level Full-Stack Software Engineer specializing in AI platforms and microservices
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About
Backend engineer currently building an AWS Lambda/FastAPI inventory recommendation system using a LangChain + GPT-4 RAG pipeline and MongoDB vector search; drove major cost optimization via Redis caching (60% reduction) while sustaining 10k+ daily requests under 2s latency. Previously deployed Node.js microservices on AWS OpenShift with Jenkins/Helm at UnitedHealth Group and led a zero-downtime monolith-to-microservices migration at Verizon, including RabbitMQ-based real-time messaging with DLQs and idempotency.
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Key Strengths
- Owned end-to-end backend architecture and API development for an inventory recommendation system
- Built and deployed a RAG pipeline (LangChain + GPT-4) with MongoDB-backed vector search
- Implemented multi-level Redis caching (embeddings + LLM responses) with TTL and inventory-triggered invalidation
- Achieved ~60% GPT-4 cost reduction with ~40% cache hit rate through similarity-based cache matching
- Scaled serverless API to 10,000+ daily requests with sub-2s response times
- Production Kubernetes/OpenShift deployment experience for Node.js microservices with HPA, probes, and monitoring
- Led monolith-to-microservices migration using strangler fig pattern and phased traffic cutover with zero downtime
- Designed reliable event-driven workflows with RabbitMQ including DLQs, backpressure controls, and idempotent processing
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