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Oleksandr Kazakov

About

AI & Data Engineer Canada Quebec Ukraine

I build large-scale data and machine learning systems, with a recent focus on GenAI, RAG pipelines, and agentic AI. Over the last few years I've deployed production LLM applications on AWS, designed multi-agent workflows, and shipped data infrastructure that processes petabyte-scale datasets in healthcare, ad-tech, and e-commerce.

I care most about the unglamorous parts of real-world AI — evaluation, reliability, cost, and what happens when the model confidently gets it wrong.

What I work on

Background

I've spent the last several years building production GenAI systems — large-scale RAG pipelines for clinical data, MCP servers for text-to-SQL flows, multi-agent workflows, and the eval infrastructure around them. Earlier work was in ML and data engineering at Gazelle AI, SSENSE, Bandsintown, and Wajam, and I taught a Big Data course at Concordia University.

PhD in Physics (All But Defence) from the University at Albany, SUNY — dissertation combined stochastic Liouville equation modeling for NMR with supervised machine learning on Raman spectroscopy data.

Publications

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