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CharanKumar Pathakamuri
Entry-Level GenAI/LLM Engineer specializing in agentic systems and RAG
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LLM/AI agent engineer with consulting/contract experience (Kanhaiya Consulting LLC) who deployed a production AI agent to automate BIM list workflows end-to-end—from database understanding and data cleaning to automated visualizations/dashboards. Worked around restricted real-time data access by generating synthetic data and improving outputs via supervised fine-tuning, and uses AWS-based LLMOps observability (Opic/OPEC) plus hybrid retrieval (vector+BM25 with reranking) to optimize relevance, latency, and cost.
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Key Strengths
- Built and deployed an AI agent automating end-to-end data workflow (DB querying → cleaning/curation → dashboards) for BIM lists
- Designed agent orchestration workflows using LangChain/LangGraph to enforce correct task sequencing and dependencies
- Handled limited/partial data access by synthesizing data to validate behavior and reduce confusion around data freshness
- Applied supervised fine-tuning to improve response quality/human-likeness
- Uses LLMOps observability (Opic/OPEC) to optimize prompts for cost and context length post-deployment
- Pragmatic model selection balancing complexity, latency, and budget (e.g., smaller models for high-volume simple tasks)
- Implemented hybrid retrieval with reranking to improve relevance despite added latency
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1 publication
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