I’m an AI Systems Architect focused on designing and building production-grade AI platforms and intelligent systems that operate reliably at scale.
My work sits at the intersection of AI/ML architecture, distributed systems, MLOps/LLMOps, and production engineering — taking systems from business requirements and data architecture all the way to models, agents, evaluation, deployment, observability, security, and cost optimization.
I specialize in evaluation-driven AI architecture, scalable ML/DL/LLM training and inference, RAG and agentic systems, model adaptation, efficient serving, and the engineering patterns required to make AI systems reliable, governable, secure, and economically sustainable.
I’m particularly interested in the difficult layer between research and production: deciding which models to use, how they should interact with data and tools, how their behavior should be evaluated, how failures should be contained, and how the overall system should scale from thousands to millions of users.
My goal is not simply to build models.
I build AI systems that can be trusted to run in production.