Landing your first dev job without professional experience

Reframe the problem: evidence, not experience

"Requires 2 years of experience" on a junior posting isn't really a demand for employment history — it's a demand for evidence that you can do the work. Employment is just the most familiar evidence. Deployed projects, open-source contributions, and a legible GitHub are alternative evidence, and for early-career screening they're often stronger, because they can be inspected directly.

The developers who break the loop stop trying to look employed and start building an inspectable body of proof.

Build one thing properly

The instinct is to accumulate projects; the market rewards finishing them. Take one project — ideally something you actually use — and push it through the boring last mile: authentication, error handling, tests, CI, Docker, deployment, and a README that explains the decisions. That last mile is precisely what tutorials skip, which is why completing it is the signal.

A deployed URL changes every conversation. It moves your project from "claims code exists" to "click and see." It also generates real engineering problems — environment config, migrations against live data, a bug report from an actual user — and those become your interview stories.

Open source is verifiable collaboration

The one thing personal projects can't prove is that you work well with others. Merged pull requests in an established project can: they show you read unfamiliar code, followed contribution conventions, and absorbed review feedback in public.

Start with projects you already use. Good-first-issue labels, documentation fixes, and failing-test reproductions are legitimate entry points — the goal is a track record of merged work, not a headline feature.

Target your applications like an engineer

Two hundred identical applications produce silence and burnout. Fifteen targeted ones — where the resume mirrors the posting's stack, the cover note references something real about the company, and your pinned repos happen to demonstrate the exact skills listed — produce interviews. Screening is a matching problem; tailoring is just improving the match score on purpose.

Track applications like experiments: role, variant of resume sent, outcome. When one version of your materials produces callbacks and another doesn't, the data tells you what to fix.

Know your score before they compute theirs

Every screening step in this guide — the GitHub review, the resume parse, the skills match — happens to you invisibly. DevProfile makes it visible first: it reads your repositories and resume the way the pipeline will, scores your hireability from 0 to 100, and hands you the ranked list of what to fix while it's still fixable.