Three ways I build dependable systems.
My experience spans cloud platforms, software delivery, and practical AI-assisted engineering. The examples below describe areas of focus and representative tools.
Infrastructure designed to run reliably.
I work with cloud infrastructure, infrastructure as code, container platforms, and operational tooling. The goal is to make environments repeatable and systems easier to operate.
Related work includes platform automation, CI/CD enablement, and production reliability. My public projects show adjacent tooling and automation work.
Automation and software that move work forward.
I build Python automation, ETL workflows, and backend services that connect data sources to useful, verifiable outcomes. Delivery practices include CI/CD, automated testing, and repeatable checks.
Go and Rust appear in my personal projects, including a local HTTP router and a file synchronization CLI.
AI workflows with checks around the output.
I use coding agents and LLM integrations to support engineering workflows, and explore agent orchestration and MCP-based tool access. These workflows need evaluation and automated verification so their results remain reviewable.
Examples include the JobHunter architecture case study and personal developer tools such as Pi Recap.