Yes, You Can Use AI in Our Interviews. In fact, we insist

Summary

Canva has updated its technical hiring process to require backend, machine learning, and frontend engineering candidates to utilize artificial intelligence tools such as Copilot, Cursor, and Claude during interviews. The transition addresses the limitations of traditional computer science fundamentals tests, which focused on writing algorithmic code from scratch even though AI assistants can generate complete solutions in seconds. To better evaluate on-the-job engineering capabilities, the company replaced its legacy screening with an AI-assisted coding competency that features complex, ambiguous product challenges such as designing an airport control system. Interviewers assess how candidates clarify requirements, guide tools on subtasks, debug flawed output, and verify that AI-generated code meets production quality standards. Candidates receive advance notice of these expectations, helping ensure prospective hires demonstrate strong engineering judgment when collaborating with assistive coding technologies.

Context

Traditional computer science fundamentals interviews asked candidates to implement algorithms and data structures from scratch without AI assistance. However, almost half of Canva's frontend and backend engineers use AI-assisted coding tools daily, and internal experiments showed that AI assistants can solve traditional interview questions in seconds, reducing the predictive signal of legacy coding tests.

Approach / What changed

Canva replaced the Computer Science Fundamentals interview with an AI-Assisted Coding competency for backend and frontend engineering roles. Candidates are expected to use tools like Copilot, Cursor, and Claude to solve ambiguous, realistic engineering challenges, allowing evaluators to assess requirement clarification, technical judgment, debugging skills, and code review capabilities.

Takeaways

• AI assistants solved traditional Computer Science Fundamentals algorithm and data structure questions in seconds during Canva's internal testing without requiring follow-up prompts.
• The AI-Assisted Coding competency replaces traditional algorithmic screenings with ambiguous problems, such as building an aircraft control system, to assess engineering judgment.
• Candidate evaluation focuses on clarifying product requirements, breaking down subtasks, identifying flaws in generated code, and maintaining production quality standards.

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