Bharat Khanna
Senior Associate Data Science @Publicis Sapient
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WORK HISTORY
Senior Associate Data Science @Publicis Sapient
Gurugram, IN
LLM-to-SLM Migration – Real-time Hierarchical Intent Detection: Replaced a large language model with a customBERT-based Small Language Model for multi-intent classification on live call transcripts, significantly reducing inference latency and cost. Designed a 3-tier hierarchical classification architecture supporting 1,800+ fine-grained intent classes, enablingaccurate real-time intent detection across complex taxonomies at production scale. Built end-to-end offline evaluation pipelines with controlled experiments to validate model improvements, driving iterativeperformance gains; achieved model accuracy exceeding 90% and delivered $1M in cap-ex savings. Enterprise Knowledge Search – RAG Platform: Architected a production-grade Retrieval-AugmentedGeneration (RAG) system enabling context-aware search across large internal knowledge repositories for support andoperations teams. Designed Model Context Protocol (MCP) server integrations to expose enterprise knowledge sources — includingdocument stores and internal APIs — as standardized tool endpoints, enabling agentic workflows to dynamically retrievecontext across heterogeneous systems without custom connectors. Implemented hybrid retrieval combining dense vector embeddings (FAISS) with BM25 keyword search, followed bycross-encoder re-ranking to maximize semantic relevance on complex multi-hop queries. Engineered scalable document ingestion pipelines with chunking strategies, metadata enrichment, and vector DB indexingsupporting heterogeneous enterprise document formats. Developed benchmarking frameworks measuring retrieval quality via Precision@k, Recall@k, and MRR; improvedPrecision@k from 75% to 90% and reduced hallucination rate by 40% through iterative optimization of the retrievalstack. Built agentic orchestration workflows using LangChain and Google ADK with multi-step reasoning, query decomposition and reduced average query response latency from 5s to 3.2s in production.
EDUCATION
Kulachi hansraj model school
XII, Science
Maharaja Surajmal Institute Of Technology
Bachelor's degree, Electrical, Electronics and Communications Engineering
ABOUT BHARAT KHANNA
Lead Generative AI & LLM Engineer with 9+ years of experience building large-scale AI systems across telecom, healthcare, and energy domains.I specialize in:→ RAG Architectures — hybrid retrieval, cross-encoder re-ranking, hallucination reduction→ Agentic AI — LangGraph, Google ADK, multi-step reasoning, dynamic tool selection→ Model Context Protocol (MCP) — enterprise knowledge source integrations→ BERT / SLM — hierarchical intent classification, fine-tuning, multi-label NLP→ LLM Engineering — prompt engineering, Azure OpenAI, semantic searchTech stack: · LangChain · LangGraph · LlamaIndex · AutoGen · CrewAI · MCP · BERT · HuggingFace · GCP Vertex AI· PythonCertifications achieved-> Azure Data Scientist (DP-100)-> Azure Fundamentals (AZ-900)-> Azure Data Fundamentals (DP-900)-> Azure AI Fundamentals (AI-900)-> Azure AI Engineer Associate (AI-102)
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