To Musinsa's Rookies

Musinsa held its first AI-native new engineer open recruitment, called Musinsa Rookiez, and selected 66 rookies.

The recruitment process consisted of a first-round online coding test, a second-round AI Agent coding test, and a third-round on-site interview. In particular, the second round presented ambiguous requirements—like a course registration system—and evaluated candidates' ability to define and design the problem themselves.

The core of this approach was to assess the ability to decide what to build, rather than implementation skill. Instead of a traditional coding test with a fixed correct answer, it checked the candidate's ability to interpret an ambiguous problem together with AI and build out its structure.

In the on-site interview, candidates were evaluated on whether they were someone to work well with, based on MUSINSA WAY criteria such as Learning Agility, Raise the Bar, and Collaborate Across Boundaries. Questions and scorecards were designed, summarized, and calibrated using AI, but the final decisions were confirmed directly by people.

The message then continues into the direction of growth after joining. In the AI era, defining problems matters more than implementation, but understanding the layers below and having domain sense are still necessary—and at Musinsa, it's emphasized that by using both colleagues and AI agents as tools, one can grow into an even stronger AI-native engineer.