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Krishna Rajput
Mid-level AI Engineer & Data Scientist specializing in LLMs, RAG, and multimodal systems
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About
LLM/GenAI engineer who built a production AI-powered credit risk policy summarization and compliance alerting platform at HCL Tech, focused on factual accuracy and auditability for a financial client. Implemented a multi-retriever LangChain RAG architecture with citations-only prompting, fallback agents, and human-in-the-loop legal review—cutting manual review time by 35% and scaling to 12 teams.
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Key Strengths
- Built and deployed production LLM risk reporting/automation platform for financial client
- Designed multi-retriever RAG pipeline with metadata filtering and fallback agents to reduce hallucinations
- Implemented citations-only output filtering for auditability in regulated finance workflows
- Integrated human-in-the-loop legal/compliance review process
- Reduced manual review time by 35% while passing internal compliance checks
- Scaled solution adoption across 12 teams
- Strong orchestration experience across AWS Step Functions and Airflow for end-to-end ML/LLM pipelines
- Structured reliability approach: success metrics, modular/version-controlled components, automated + human eval, monitoring and drift detection
- Effective collaboration with non-technical compliance stakeholders via workshops, prototypes, and weekly feedback loops
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Experience
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Publications
1 publication
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