Julian Patton, AI Engineer and Data Scientist

This site is the professional home of Julian Patton, an AI engineer and data scientist based in Washington, D.C. Its purpose is straightforward: to document the work, the thinking, and the ongoing education behind practical AI product development in one place that is easier to share than a handful of scattered profiles and resumes.

It is written for a specific audience. Hiring managers and technical recruiters evaluating AI and data talent belong here. So do engineering leads looking for someone who can carry an AI concept from prototype through to a working product, and fellow practitioners and career changers who want to see how a data career actually develops from the inside rather than in hindsight.

Everything on the site is built and maintained by Julian himself. He currently works as a Data Analyst at the DC Housing Authority and is completing an M.S. in AI Engineering at Quantic School of Business and Technology, with an expected graduation of September 2027. His technical background spans machine learning, statistical modeling, and data visualization, supported by dual postgraduate certifications from the University of Texas at Austin's McCombs School of Business: one in AI and Machine Learning for Business Applications, and one in Data Science and Business Analytics.

Visitors will find professional experience across IT operations, government technology, and analytics; a detailed skills profile covering Python, SQL, machine learning, and modern LLM work with LangChain and retrieval-augmented generation; selected projects with the results they produced; and Insights, a blog where longer-form writing on AI engineering, cloud foundations, prompt engineering, and career transitions lives.

The intent behind publishing that writing publicly is to contribute citable, readable, practical knowledge rather than marketing copy. If you are trying to judge whether the technical depth matches a role description, the articles are the fastest way to do it.

For roles, collaborations, or consulting engagements involving AI engineering, data analytics, or LLM integration, get in touch.