I am an adaptable and results-driven AI Engineer and Data Scientist focused on building production-ready systems, from RAG pipelines and memory architectures to LLM-driven workflows.

I’m especially interested in the harder parts of these systems, how memory carries across interactions, how agents safely use tools, and how retrieval stays reliable when the data gets messy. Most of the work I enjoy lives in that space between prototype and production, taking ideas and making them robust enough to actually ship.

With a solid foundation in data science, working on large-scale datasets and modeling problems, it still shapes how I build today, focusing on evaluation, scalability, and real-world impact.