About

I'm a software engineer who likes working where architecture, product thinking, and execution all meet. Over the years, that has meant building backend services, event-driven systems, and user-facing tools that help teams move faster without making the system harder to reason about.

My day-to-day instincts are pretty consistent: simplify the shape of the problem, make the data model pull its weight, and keep the path from idea to working software as short as possible. That has taken me from APIs and Spring Boot gateways to Angular frontends, config-driven interfaces, MongoDB-backed workflows, and the operational work around shipping software with confidence.

Lately, a lot of that curiosity has been flowing into AI engineering. I'm interested in the practical side of it: MCP servers, LLM tooling, retrieval, automation, and the design choices that make AI systems actually useful instead of merely flashy. I tend to learn in public, whether that's through tutorials, experiments, notebooks, or writing that turns a technical concept into something another engineer can apply quickly.

Outside the terminal, I recharge with biking, tennis, and the kind of side-project ideation that starts as a small curiosity and occasionally turns into a real build. That mix keeps me grounded and keeps the work interesting. The throughline across all of it is simple: I like learning fast, building carefully, and leaving systems better than I found them.