Architecture Technique

Production AI systems fail for architecture reasons, not algorithm reasons. The model works in the notebook but breaks in production because nobody designed for latency, failure modes, or data drift. I design AI architectures that handle the real world.

This includes agent architectures for autonomous operations, vector search systems for knowledge retrieval at scale, decision engines that make real-time judgments with auditable reasoning, and data pipelines that handle edge cases without silent failures.

I work at the intersection of reliability engineering and AI. Every system I design includes monitoring, graceful degradation, and clear failure boundaries. The goal is AI infrastructure you can trust to run without constant human intervention.