About

I started out as an SDET and I'm now moving into Applied AI, turning good models into useful, reliable features. Lately that means agent workflows and RAG: small services, clean APIs, and connectors that fit cleanly into existing stacks. I aim for predictable behavior and clear boundaries.

I came up through testing and automation. I built UI/API test frameworks, hardened CI, and did a lot of browser automation. That background still shapes how I design systems today: simple interfaces, clear contracts, fast signals when something breaks. You can find my professional experience on LinkedIn.

Tech Stack

I work mostly in Python, sometimes TypeScript and Go. I ship services with FastAPI, store data in PostgreSQL, use Redis for cache and queues, and package with Docker. I use LLM tooling like LangChain or LlamaIndex when it fits, with vector stores for retrieval. I often self-host for control, cost, and observability. I've spent a fair bit of time scaling Playwright. I like boring, dependable pieces that fit together and keep running.

I also poke around in open source, you can find my work on GitHub. The main one is playwright-distributed, a self-hosted setup for scaling Playwright when you need reliable browser automation at volume.

Get In Touch

If you're building practical AI features or dependable automation and want someone who plugs in quickly, keeps things tidy, and ships steadily, say hi: [email protected]