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Bharat Potluri
Senior Machine Learning Engineer specializing in LLMs, RAG, and agentic AI systems
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LLM/RAG practitioner who has taken a support-ticket triage automation system from prototype to production, building the full pipeline (fine-tuned models, FastAPI inference services, vector storage, monitoring) and delivering measurable impact (~40% reduction in triage time). Demonstrates strong operational troubleshooting of LLM/agentic workflows (observability-driven debugging, fixing agent routing/looping) and supports adoption through tailored demos and sales-aligned technical communication.
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Key Strengths
- Built end-to-end RAG-powered support automation from prototype to production
- Reduced ticket triage time by ~40% through automation
- Improved retrieval quality and reduced hallucinations in production LLM workflows
- Performance optimization (latency reduction via caching and API profiling)
- Strong real-time debugging using observability signals (latency, hit rates, confidence, prompt/embedding/data changes)
- Diagnosed and fixed agent looping by tracing tool calls and correcting routing logic
- Able to tailor technical demos for engineering, product, and data science audiences
- Effective pre-sales partnership: translating technical feasibility/tradeoffs into business value to drive adoption
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