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Amaan Elahi
Mid-level Software Engineer specializing in backend, AI, and full-stack systems
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About
Built and shipped production LLM agents including an internal RAG-based compliance classification system at SAIL (FastAPI/Redis/Docker) designed to handle real failure modes and scale to ~10k LLM calls/hour, achieving ~93% pipeline accuracy with reduced hallucination risk via multi-model orchestration and strict grounding. Also architected “Elara,” a state-machine-driven conversational appointment booking agent using structured JSON outputs and backend function execution for reliability, and has experience normalizing messy OTA/PMS data at RateGain.
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Key Strengths
- Shipped production LLM agent with reliability engineering (retries, rate limiting, idempotency) at scale (~10,000 LLM calls/hour)
- Improved compliance RAG pipeline accuracy to ~93% and increased throughput while reducing hallucination risk via grounding
- Designs predictable agent systems by limiting LLM control to intent/next-step decisions and using backend function execution
- Strong evaluation/monitoring approach: offline test sets + step-level logging/metrics to isolate failures by layer
- Improved system accuracy by diagnosing retrieval as root cause and enhancing chunking + re-ranking (without changing the model)
- Experience hardening integrations against messy operational data via normalization, validation, idempotency, and guardrails
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