AI Engineer at The Philadelphia Inquirer. I build production systems that bring natural language to journalism — archives, audiences, and infrastructure that lasts.

The Inquirer's Digital Librarian
A conversational AI interface that lets journalists and editors query 47 years of the Inquirer's article archive in plain English — and receive cited, sourced answers in natural language. Built on a multi-agent RAG architecture. Read more →
Hyperlocal newsletters at scale
An AI-powered aggregator enabling the Inquirer to produce hyperlocal newsletters for communities across the Philadelphia region that were previously out of reach — surfacing relevant local stories automatically.
I'm an AI Engineer with a background in Explainable AI— the discipline of making machine learning systems transparent, interpretable, and trustworthy. I've spent the last few years applying that foundation inside one of America's most storied newsrooms, building production systems that let language models do real, consequential work.
“The most powerful AI systems are the ones that show their work.”
My work spans the full stack: indexing pipelines, retrieval architectures, agentic systems, and the UX that makes AI legible to non-technical stakeholders. I care deeply about the gap between a model that performs well on benchmarks and one that earns trust in production.
I'm now looking for my next chapter — roles at the frontier of applied AI where interpretability, reliability, and real-world impact aren't afterthoughts.
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