Presentation
My philosophy centers on high-agency, systems-first engineering. I believe the key to reliable AI is strictly separating an LLM’s creative reasoning from deterministic business logic. By leveraging state graphs and orchestration frameworks like LangGraph, I tame LLM variability to build robust, predictable multi-agent workflows.
I bridge the gap between advanced AI capabilities and scalable full-stack infrastructure. From designing complex RAG architectures with pgvector to deploying and optimizing local open-source models, I build the end-to-end systems that bring AI concepts into production reality.
Core Stack & Focus Areas:
AI/ML: Agentic AI, Multi-Agent Systems, LangGraph, RAG Orchestration, Local Model Deployment, Custom AI Pipelines.
Engineering: Python, FastAPI, Next.js, AI-native development workflows.
Domain Expertise: Automating complex business logic, from intelligent quoting engines to advanced visual automation.

