I am a self-taught Full-Stack Engineer who started building software by teaching myself how things work from the ground up. Over the years, that grew from building web applications into designing backend systems, APIs, databases, automation pipelines, and production workflows that solve real problems.

Today, I work across TypeScript, Python, and Go, building full-stack products, backend services, event-driven automation systems, and containerized workflows. I am comfortable moving between application code, databases, APIs, infrastructure, testing, and deployment rather than being limited to a single layer of a system.

More recently, my work has expanded into AI engineering and evaluation. I have worked with AI data platforms and software engineering evaluation environments, reviewing AI-generated implementations, debugging failures, designing edge cases, building verification logic, and creating benchmark tasks for realistic engineering scenarios. This has pushed me to think beyond whether something simply works and focus more on why it works, how it fails, and how reliably that behavior can be verified.

I have also built reusable automation infrastructure rather than repeatedly solving the same integration problem from scratch. Projects such as Adulis and Damtie have involved event-driven processing, APIs, databases, workers, containerized services, and integrations across different sources and destinations.

My focus now is on building reliable systems and working on problems where software engineering, automation, and AI meet. I care about understanding the underlying system, finding failure points, and building solutions that continue to work beyond the happy path.