AI Engineering Leader · Computational Scientist
Victor Murcia, PhD
AI Engineering · Scientific Computing · Technical Leadership
I build and lead production AI systems for complex scientific and enterprise problems. My background spans computational physics, machine-learning research, medical and federal AI, and scientific software — a throughline of using computation to make hard problems tractable.
Read the research AI & engineering work
AI Systems & Engineering
Production AI, built to be reliable
LLM systems, document and multimodal intelligence, retrieval and agentic workflows — and the evaluation that keeps them dependable in production.
EngineeringScientific Research
First-principles computation meets ML
Quantitative, physically interpretable methods bridging DFT, spectroscopy, and machine learning — including first-author work accepted to Physical Review Letters.
ResearchTechnical Leadership
Architecting and leading delivery
Setting AI architecture and technical direction, and leading engineers to ship production systems across enterprise and scientific software.
AboutFeatured research
Quantitative and bond-traceable resonant X-ray optical tensors of organic molecules
A first-principles-to-experiment method that makes resonant soft X-ray scattering quantitative — resolving the orientation of individual chemical bonds inside molecular nanostructures.