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Hemanth Suddala
Mid-level GenAI Engineer specializing in LLM automation, RAG, and document intelligence
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About
Built and deployed a production GenAI resume screening and matching system for Florida Atlantic University, focused on improving recruiter efficiency and search relevance. Demonstrates strong RAG engineering (embeddings, query rewriting, metadata filtering, threshold tuning) plus practical reliability work (grounding constraints, fallbacks, and evaluation using real user queries) using Python REST APIs and orchestration frameworks like LangChain and LlamaIndex.
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Key Strengths
- Built and deployed production LLM resume screening/matching system (Florida Atlantic University)
- Strong RAG retrieval optimization (embeddings, similarity thresholds, metadata filtering, query rewriting)
- Grounding and hallucination reduction via prompt constraints and confidence-based fallbacks
- Structured agent/workflow design with staged architecture (retrieval → construction → inference → post-processing)
- Reliability evaluation using curated datasets, edge cases, and production metrics (precision, relevance, latency, fallback rate)
- Hands-on orchestration with LangChain and LlamaIndex for RAG pipelines
- Effective collaboration translating non-technical stakeholder needs into workable GenAI workflows
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