Building production-grade

Agentic AI & LLM Systems

I'm a GenAI Engineer and LLM Systems Architect based in New York, specializing in building AI systems that ship to production.

My core work sits at the intersection of agentic AI, RAG architecture, and LLM engineering. I design and deploy systems using LangGraph, CrewAI, LlamaIndex, and MCP (Model Context Protocol) for tool integration, with evaluation pipelines built on LangSmith and Ragas to ensure they hold up at enterprise scale.

My ML foundation runs deep. I built fraud detection and anomaly scoring systems that improved accuracy by 47%, data pipelines that cut processing time by 60%, and predictive models reducing forecasting errors by 35%, all integrated into production applications via FastAPI, Docker, and AWS.

At Yeshiva University I teach graduate engineers how to architect these same systems. This covers agentic workflows, vector retrieval, transformer fine-tuning, and responsible production deployment. The best way to sharpen what you know is to teach it.

I hold an M.S. in Data Analytics and Visualization from Yeshiva University and a B.Sc. (Honors) in Business Studies and Computing Science from the University of Zimbabwe.

I am open to GenAI Engineer, LLM Engineer, ML Engineer, and Data Scientist roles where the work is real, the problems are hard, and the systems actually get used.