Harsh Mehta is an AI Engineer in Charlotte, NC with 5+ years across data science and machine learning, including 2+ years shipping production LLM systems. He currently builds RAG and LangGraph agent systems at Kaiser Permanente.

What does Harsh Mehta do at Kaiser Permanente?

He builds citation-backed RAG over 5,000+ pages of compliance documentation, with LangGraph agents and human-in-the-loop review. The work cut a 3-month policy review to one week and reclaimed roughly 300 analyst-hours per cycle.

Does Harsh Mehta have LangChain and LangGraph experience?

Yes. He has shipped LangGraph and LangChain multi-agent systems in production, including agent orchestration at Kaiser Permanente, the multi-agent core of the Ensemble booking platform on Vertex AI, and 7 multi-agent LLM workflows at ATC.

Is Harsh Mehta open to new roles?

Yes. He is open to AI Engineer, Machine Learning Engineer, and Data Scientist roles in Charlotte, NC and remote across the US.

Where did Harsh Mehta go to school?

He holds an M.S. in Information (Data, Machine Learning, Cloud) from the University of Wisconsin-Madison with a 3.95 GPA, and a Bachelor of Management Studies from the University of Mumbai with a 3.5 GPA.

What certifications does Harsh Mehta hold?

He holds the Databricks Data Engineer Associate, Snowflake SnowPro Core, Azure DP-100, Power BI PL-300, and AZ-900 certifications (all 2025), plus Salesforce Tableau.

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Actuarial ML · 2026 · XGBoost / LightGBM

Healthcare Premium Predictor

An actuarial ML pipeline predicting health-insurance premiums from 750,000 records, using segmented XGBoost and LightGBM models with 5-fold cross-validation and engineered risk-score and income-plan interaction features.

R² 0.9976 on the adult segment, served through a Streamlit UI with confidence ranges, plan comparison, and a payment breakdown.

XGBoostLightGBMStreamlitFeature EngineeringML

View on GitHub Live demo