Jaya Sabarish Reddy Remala

Production AI portfolio with Avocado, a streaming RAG chatbot backed by a 4-stage hybrid retrieval pipeline: query expansion (up to 4 variants), batched dense search via ChromaDB (all-MiniLM-L6-v2 ONNX), BM25 lexical search (rank_bm25), and Reciprocal Rank Fusion (k=60) — all before Gemini 2.5 Flash sees the question. Knowledge base of ~80 atomic documents auto-syncs incrementally: new or edited documents are upserted, deleted documents are purged from ChromaDB, unchanged ones are skipped entirely. Runs as a FastAPI Docker container on AWS Lightsail with zero-downtime blue-green deployments, Nginx + Let's Encrypt HTTPS, daily S3 backup of SQLite analytics, and a Next.js 16 static frontend on GitHub Pages — total cost $10/month.

Achieved 15ms token latency on Snapdragon NPUs — a 10× improvement over cloud inference — by fine-tuning Llama 3.2 3B on security logs with QLoRA and deploying via 4-bit AWQ quantization through ONNX Runtime on-device. Guaranteed zero data loss during network partitions via an offline-first SQLite buffer with background sync workers.

Production LangGraph + Llama 3.1 70B system that semantically maps global researcher collaboration networks by indexing millions of papers from Elsevier's Science Direct/Scopus. Cut P99 RAG latency by 78% with Write-Through Redis caching; sustained 99.9% uptime at 3,000+ RPS on AWS ECS.

Conflict-free simultaneous multi-user editing using Yjs (CRDTs) and WebSockets, scaled horizontally via Nginx load balancing across containerized instances. Increased AI auto-complete context quality by 65% with a Context-Aware Coding Agent using AST-based chunking and Voyage-Code-2 embeddings.