Two candidates describe Adyen's AI Engineer interviews as a recruiter call, manager conversations, and in one case a Python coding task and a leadership round. Both received no offer.
$205K
Avg. Base Comp
$260K
Avg. Total Comp
3-5 rounds
Typical Rounds
Not reported
Process Length
Two candidates describe Adyen's AI Engineer process, and their accounts differ in length and format, so treat the details below as reports from individuals. Both candidates said the process started with a recruiter conversation about their background, and one was asked directly whether they had done AI work. Be ready to talk concretely about AI projects you have built, including your own role and the decisions you made.
One candidate described a longer sequence: a recruiter video call, a peer interview on prompt engineering and basic LLM concepts, a manager interview, a Python assignment to implement a dot product, a task review where the interviewer walked through the code, and a final leadership interview. They said the assignment took longer than expected and that edge cases and efficiency mattered. Practice writing simple numeric functions cleanly, and be ready to explain your reasoning aloud.
The same candidate said the leadership round probed management philosophy, team dynamics, and strategic thinking, even though the role was presented as technical. The other candidate described a hiring manager conversation of under 30 minutes, followed by another round the next week. They found the questions repetitive and the AI emphasis stronger than the job listing suggested. Both reports point to consistent, well-rehearsed answers about your background and motivations. Also ask the recruiter early how many stages there are, what each covers, and how much of the day-to-day work is AI-focused. Both candidates were rejected.
Synthesized from 2 candidate reports by our editorial team.
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Real interview reports from people who went through the Adyen process.
The recruiter called weeks after I applied and first asked about my background and whether I had done AI work. That led to a hiring manager conversation lasting under 30 minutes, followed by another round the next week. The process was described as three stages, although the structure did not feel clear because similar questions recurred and each round could seem like the final one before another interviewer was added. AI was discussed extensively even though the job listing mentioned little about it, so the role felt different from what I applied for. The questions and comments suggested a high degree of independence from day one. I did not receive an offer. Ask directly what the day-to-day work involves and how much is genuinely AI-focused versus adjacent work.
Prep tip from this candidate
Be ready to speak concretely about AI work you have done, since that was the main screening question. Ask early how many stages there are and what each is meant to cover, because the rounds felt repetitive and the role description did not match the AI emphasis in the interviews.
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Featured question at Adyen
In which case would you use a bagging algorithm versus a boosting algorithm
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| Dot Product | |
| Swipe Payment API | |
| Text Editor With OOP | |
| Why Do You Want to Work With Us | |
| Decreasing Tech Debt | |
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| Get Top N Frequent Words | |
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| Justify a Neural Network |
Synthesized from candidate reports. Individual experiences may vary.
Both candidates report starting with a recruiter conversation about their background. One was asked directly whether they had done AI work, and that answer shaped the next step. Prepare a concise, concrete account of AI projects you have delivered and your own contribution.
One candidate reports a video peer interview on prompt engineering and basic LLM concepts. The other describes a hiring manager conversation under 30 minutes, followed by another round the next week. Formats vary, so expect questions on your AI work and fundamentals, and ask the recruiter what each stage covers.
One candidate describes a manager interview that was conversational but still focused on technical depth. The other reports similar questions recurring across rounds. Candidates may do best with consistent, practiced answers about core concepts and career motivations.
One candidate reports a substantial take-home style assignment to implement a dot product in Python, which took longer than expected and needed attention to edge cases and efficiency. A follow-up review round walked through the code and asked about their approach and reasoning. Be ready to defend your choices.
One candidate reports a final leadership interview covering leadership philosophy, team dynamics, and strategic thinking, which felt different from the technical framing of the role. Prepare examples of influence, ownership, and decision-making, even if applying for an individual contributor position.
