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Harish Gaddam
Mid-level AI/ML Engineer specializing in LLM agents and RAG systems
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About
LLM/agentic systems builder at Verizon who deployed a LangGraph-orchestrated multi-agent ticket-automation platform with RAG (FAISS) to replace brittle rule-based bots. Improved routing correctness by ~30–40%, hit ~300ms latency targets via model routing, and reduced ops workload by ~60% through tight iteration with non-technical stakeholders and strong testing/observability practices.
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Key Strengths
- Built and deployed production multi-agent LLM ticket-automation system at Verizon
- Reduced hallucinations and improved correctness ~30–40% via hybrid retrieval, metadata filters, relevance scoring, and grounded/structured outputs
- Achieved ~300ms response latency using model routing (small models for simple tasks, larger models when needed) and system optimization
- Strong reliability engineering for LLM workflows (unit/regression/load tests, synthetic edge-case evals, observability, drift monitoring, versioning and A/B rollouts)
- Effective collaboration with non-technical operations stakeholders; iterated prototypes and incorporated feedback to capture undocumented edge cases
- Delivered ~60% workload reduction for ops team through AI-driven ticket workflow automation
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