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Level: Intern
Round: Full Journey · Type: Multiple Types · Difficulty: 5/10 · Duration: 120 min · Interviewer: Unfriendly
Topics: Behavioral Questions, Depth-First Search, Hashmap, Generative AI, Time Complexity, Space Complexity
Location: Seattle, WA, US
Interview date: 2026-03-23
I applied for a software engineering internship at Amazon. My interview experience consisted of two virtual onsite interviews.
Virtual Onsite 1: My first interview was with an interviewer who didn't talk much but was a good person. It was structured as 30 minutes of behavioral questions and 30 minutes of coding, with time for me to ask questions. I answered at least five behavioral questions. Besides common generative AI-related questions, I was asked almost all the behavioral questions that can be found online. For the coding question, I received a standard depth-first search variant question. I didn't achieve a bug-free solution and had to modify my code iteratively. The interviewer provided hints and guidance. I also discussed the time and space complexity of my solution.
Virtual Onsite 2: My second interview was with a very nice and talkative interviewer. It consisted of 55 minutes of behavioral questions with follow-ups and 5 minutes of coding. This round felt more like a conversation. It mainly focused on two major questions: my proudest project and my experience using generative AI. Whenever I mentioned something interesting, the interviewer would politely interrupt to ask further questions. The discussion covered my thesis, project experience, general behavioral questions, basic knowledge of large models, and AI-related courses I had taken. For coding, I described my approach to an easy hashmap problem, then discussed the approach and time complexity for a medium variant of the hashmap problem.