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HIMANSHU SHARMA
Mid-level AI Solutions Engineer specializing in enterprise GenAI and automation
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Built and shipped multiple production LLM/agentic systems, including an agentic RAG NL-to-SQL analytics app that cut manual reporting from 9 hours/week to 15 minutes by grounding on schema-aware retrieval and robust fallback/monitoring. Also implemented a LangChain supervisor-orchestrated enterprise IT automation agent that routes requests for search, identity validation, and action execution, and created a RAG search tool spanning Jira/Confluence/SharePoint for operations stakeholders.
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Key Strengths
- Built and deployed production agentic RAG NL-to-SQL reporting system reducing analyst reporting time from 9 hours/week to 15 minutes
- Strong reliability engineering for LLM systems (guardrails, schema grounding, syntax checks, monitoring/logging)
- Designs effective fallback UX (clarifying questions + retry/rethink loop for SQL generation) to avoid bad outputs
- Hands-on agent orchestration in production using LangChain supervisor-style routing with permission/context-aware workflows
- Data-driven evaluation of agent workflows using operational KPIs and iterative improvement from logs/traces and failed cases
- Effective collaboration with non-technical stakeholders by demoing value quickly and iterating based on feedback
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