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Lakshmi Narayana
Mid-level Data Science AI/ML Engineer specializing in Generative AI, LLMs, and RAG systems
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About
Built a production RAG-based "knowledge copilot" for support/ops using LangChain/LangGraph, implementing the full pipeline (ingestion, chunking, embeddings, vector DB retrieval/rerank, guarded generation with citations) and operating it as monitored microservices with CI/CD. Also designed an event-driven, streaming backend for real-time inventory ordering predictions that reduced stockouts by 25%, and has hands-on incident response experience stabilizing LLM API latency/5xx spikes using Datadog/APM and resilience patterns.
Experience
Key Strengths
- Built and deployed production RAG knowledge copilot end-to-end (ingestion through API microservices)
- Reliability/performance engineering for LLM systems (monitoring, CI/CD, caching, indexing) with ~99% reliability
- Strong approach to ambiguous problem scoping via stakeholder interviews and success metrics
- Reduced hallucinations by enforcing evidence/citations and branching to clarifying/escalation paths
- Designed scalable event-driven backend for real-time inventory prediction; reduced stockouts by 25%
- Production incident debugging using Datadog/APM/logs; mitigated p95 latency and 5xx spikes with timeouts and bulkheads
- Continuous improvement loop using offline regression sets plus production telemetry
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