Professional Overview
Python engineer building LLM-powered systems end-to-end: multi-provider model orchestration with cost-aware routing, multi-agent debate/ensemble pipelines, a from-scratch MCP (Model Context Protocol) server, and hybrid RAG retrieval (dense pgvector + lexical BM25). All in async Python, deployed on Linux. Strong quant/data foundation too — real-time
Areas of Expertise
Automation & AI Workflows
Build intelligent automation pipelines, integrate AI APIs into existing tools, and replace manual workflows with agentic AI systems.
AI Product & Strategy
Translate AI capabilities into product roadmaps, define success metrics, and drive adoption across engineering and business teams.