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Manmeet Kumar

Manmeet Kumar

Gen AI Engineer

Talent
BengaluruMember since April 26, 2026
Fine-tuning (LoRA, QLoRA, PEFT)RAG (chunking, retrieval, re-ranking)Structured promptingEvaluation pipelinesGuardrailsHuggingFace TransformersMulti-agent architecturesAutoGenLangChainLangGraphPlanner–executor–validator workflowsStateful AI pipelinesEmbeddingsVector searchHybrid retrievalAzure AI SearchSQLPySparkETL pipelinesData modelingAzure OpenAIAzure MLDatabricksFastAPIDockerPythonJava
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Fine-tuning (LoRA, QLoRA, PEFT)RAG (chunking, retrieval, re-ranking)Structured promptingEvaluation pipelinesGuardrails

About

Generative AI Engineer focused on building production-grade LLM systems, agentic workflows, and RAG pipelines. Experienced in designing multi-agent architectures (AutoGen, LangGraph), fine-tuning models using PEFT (LoRA/QLoRA), and implementing evaluation-driven pipelines with guardrails and validation layers. Strong emphasis on execution, rapid prototyping, and deploying scalable AI systems in enterprise environments using Azure.

Experience

Data Scientist at Mercedes-Benz Research and Development India (2023-08 – Present)

Designed and deployed production-grade LLM systems automating engineering workflows, moving solutions from prototype to enterprise-scale deployment.

  • Designed and deployed production-grade LLM systems automating engineering workflows, moving solutions from prototype to enterprise-scale deployment.
  • Built multi-agent systems (planner–executor–validator) using AutoGen and LangGraph-style orchestration for solving complex, multi-step business logic.
  • Developed hybrid RAG pipelines with embedding retrieval, chunking strategies, and re-ranking to improve factual accuracy and reduce hallucinations.
  • Implemented guardrails, validation pipelines, and evaluation frameworks (automated + human-in-loop) to ensure reliable and safe LLM outputs.
  • Optimized LLM pipelines for latency, token efficiency, and cost, enabling scalable and production-ready deployments.
  • Co-inventor on a filed patent related to AI-driven automation of manufacturing planning workflows using LLM-based architectures.

Education

B.Tech in Computer Science Engineering – VIT Bhopal (2019 – 2023)

Skills

Gen AI Engineer

Reviews

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