Nordeus Replaced Algorithm Puzzles with Real Game-Feature Interviews

Nordeus had been using the standard technical-interview playbook: abstract algorithm and data-structure questions that candidates could spend weeks rehearsing. The company concluded that this format was disconnected from the everyday work of experienced engineers building complex, scalable software.

It split the loop by experience. Juniors receive smaller, focused problem-solving tasks; experienced engineers work directly on a real video-game feature. Their loop has two 90-minute sessions: staged hands-on coding plus code review, followed by system design tailored to the candidate's domain, such as backend or frontend/client architecture for a live leaderboard.

The interview is designed as collaborative work rather than a gotcha test. Candidates can use Java, C#, or Python, while interviewers look for clean architecture, maintainability, communication, edge cases, and explicit trade-offs. In the daily-quest example, a strategy interface lets the engine evolve from additive progress to resettable progress without embedding each quest rule in the core; a completion guard prevents repeat rewards.

Make the interview a collaborative slice of the job

Algorithm drills rewarded preparation for a narrow test, not necessarily the practical craft Nordeus needed.

A real feature exposes decomposition, maintainability, edge-case handling, and collaboration together.

Role-specific system design avoids irrelevant questions, such as asking a frontend engineer to rehearse backend scaling trivia.

Collaborative prompts reveal how candidates clarify ambiguous requirements and explain trade-offs.

For experienced specialists, make assessment resemble the job: use realistic tasks, tailor system design to the role, and judge clarification and trade-offs instead of demanding one canonical answer.

Nordeus's current process for experienced engineers is two collaborative technical sessions with little special preparation and no hidden traps. The source documents the design and examples of the loop, but gives no hiring-volume or quality-of-hire metrics; the defensible result is a closer alignment between the assessment and the job.