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vishal varma
Mid-level Generative AI Engineer specializing in LLMs, RAG, and MLOps
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Built and deployed a production RAG-based LLM Q&A and summarization platform for internal documents, emphasizing grounded answers with structured prompting and citations to reduce hallucinations. Experienced orchestrating end-to-end LLM workflows with LangChain plus cloud pipelines (Azure ML Pipelines, AWS), and runs iterative evaluation using both metrics (accuracy/hallucination/latency/cost) and real user feedback to drive reliability.
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Key Strengths
- Built and deployed a production LLM Q&A + summarization platform over internal documents
- Designed end-to-end RAG architecture (chunking, embeddings, vector DB, retrieval + structured prompting)
- Improved trust/accuracy by tightening prompts and adding citations to reduce hallucinations
- Iterative evaluation loop combining quantitative metrics with real user feedback
- Hands-on orchestration of LLM workflows with LangChain; standardized retrieval/context injection for consistency
- Pragmatic about scaling: identified LangChain performance/control limits and replaced/optimized components with custom code
- Strong ability to translate business needs into AI solutions and keep non-technical stakeholders aligned via demos/check-ins
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1 publication
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