Non SDE intern applicants have rated the interview process at Amazon with 3.7 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 67% positive. To compare, the company-average is 63.4% positive. This is according to Glassdoor user ratings.
Candidates applying for Non SDE intern roles take an average of 60 days to get hired, when considering 3 user submitted interviews for this role. To compare, the hiring process at Amazon overall takes an average of 38 days.
Common stages of the interview process at Amazon as a Non SDE intern according to 3 Glassdoor interviews include:
One on one interview: 50%
Skills test: 50%
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I got an interview invite a month after passing the oa. there were two interview rounds. I got asked some leetcode mediums and an ai assisted coding question. behavioural questions were pretty standard.
I applied online. The process took 10 months. I interviewed at Amazon (California City, CA) in Apr 2026
Interview
One coding question and several behavioral questions. The coding problem was unconventional and differed from standard algorithmic questions, requiring creative thinking and problem-solving rather than typical data structures or patterns.
I applied through college or university. I interviewed at Amazon (Bengaluru) in Mar 2026
Interview
I recently had the opportunity to interview with Amazon. The process consisted of a technical round that evaluated both my problem-solving skills and my understanding of modern technologies.
In the DSA section, I was asked a question based on partition dynamic programming. The problem required identifying optimal ways to divide a structure (such as an array or string) into segments and applying DP to compute the best result. I approached it by defining a state, exploring all possible partitions, and building a recurrence relation. The interviewer focused on my thought process, clarity in explaining transitions, and time complexity analysis.
In addition to DSA, I was also asked several Generative AI theory questions. These included concepts like Large Language Models (LLMs), differences between traditional machine learning and generative AI, and practical ideas such as Retrieval-Augmented Generation (RAG) and hallucinations. The discussion emphasized conceptual clarity and real-world applications rather than deep theoretical details.
Overall, the interview experience was positive and well-structured. The interviewer was attentive to my approach and encouraged clear communication throughout the discussion.
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