1. Company and Role

• Company: Amazon

• Role: SDE Intern (Winter internship)

• Batch/Year of Graduation: 2027

• Eligibility: All branches,

• CGPA: 6.5 CGPA and above (No active backlogs)

• 10th & 12th: 60% and above

2. Application Process

• How did you apply? => On-Campus

• Timeline:

  • Application Date: 6 Aug 2026

  • Online Assessment Date: 20 Aug 2026

  • Interview Dates: 18 Sept 2026

3. Selection Process : 1 OA + 2 Technical interviews

Round 1: Online assessment - On-campus

• Type: Coding + managerial simulation

• The first round was an Online Assessment consisting of two main sections: a coding assessment and a managerial/behavioral simulation.

  1. Coding Assessment:
  The coding section included one DSA-based coding problem along with a backend-oriented problem. For the backend problem, a pre-existing codebase was provided in the programming language of the candidate’s choice, such as Node.js, Java, C++, etc. The task involved understanding the given codebase, implementing the required features, and identifying and fixing bugs based on the problem statement.

  A chatbot was also available during this section, which could be used to get hints, clarify the problem, or review the code. However, it did not provide direct solutions, so the candidate had to understand the problem and implement the solution independently.

  2. Managerial Simulation and Behavioral Assessment:
  The second section was a managerial simulation designed to assess decision-making and workplace behavior. It included situations where we had to respond to emails by selecting appropriate responses, arrange different strategies in order of effectiveness, and rate the effectiveness of different approaches on a scale ranging from least effective to most effective.

  There were also behavioral questions focused on workplace preferences and situations, such as whether you work better independently or as part of a team. These were generally presented as pairs of statements, where we had to select the statement that was more representative of our working style.

• Difficulty Level: Easy-medium

• Your Experience: The behavioral questions carried significant weight in my experience, so be familiar with Amazon’s 16 Leadership Principles and prepare examples from your own experiences that demonstrate them.

Round 2: Technical Interview 1

The first technical interview was conducted by an interviewer with around 14 years of industry experience, including 10 years at Amazon.

At the beginning of the interview, the interviewer explained the overall agenda. The interview was structured approximately as follows:

• Introduction and discussion about our backgrounds

• One coding/DSA problem

• Leadership Principles and behavioral questions

• Candidate questions and conclusion

The interview began with the interviewer introducing himself and briefly describing his experience, followed by my introduction.

I was then given a graph/grid-based DSA problem, similar to LeetCode 79 (Word Search). I was given some time to understand and process the problem. I explained that I was considering a DFS/backtracking approach, where I would recursively explore the grid while matching the characters of the given word.

The interviewer first asked me about the time complexity of my proposed approach and discussed the reasoning behind it.

I was then asked to write the solution in “production-grade quality” on paper. While writing the code, I asked a few clarifying questions whenever I encountered ambiguities, which the interviewer patiently addressed.

After completing the code, instead of immediately explaining it, I was asked to perform a dry run on paper. I worked through the execution and then explained the code, including the logic, execution flow, and complexity.

During the discussion, the interviewer pointed out a few edge cases and asked how my implementation would behave in those situations. I realized that the initial implementation would fail for some of these cases. I then thought through multiple possible approaches to handle them and discussed them with the interviewer. He provided a few subtle hints when required, and through the discussion I was eventually able to arrive at a correct and robust solution.

The coding discussion was followed by questions about one of my hackathon projects, which I had developed as part of a three-member team. The questions focused on both my technical contribution and my ability to work within a team. Some of the questions included:

• What was your role in the team?

• What were your technical and non-technical contributions?

• Can you explain the dataset used in your ML project?

• How did you convince your teammates to use a synthetic dataset?

• How did you handle tight deadlines?

• How did you collaborate with your team members?

The interviewer was interested not only in the technologies used in the project, but also in the reasoning behind my decisions, ownership of my work, teamwork, and how I handled challenges.

Towards the end, I was given an opportunity to ask questions. I asked about the role, his experience at Amazon, and a few questions about working at the company. The interview then concluded.

• Difficulty Level: Medium-Hard

• Your Experience: The “writing code on paper without mistakes” is what makes this round pretty hard. Make sure you know how to write code on a blank paper with proper syntax, structure and meaningful variable and function names. As for the behavioural questions, most important thing is confidence. The interviewers will test you with questions that might waver your confidence, but it’s important that you stick to your answers and “own” what you did. Be prepared with a few STAR stories ( you can google this.. it’s a way to answer behavioural questions), and communicate clearly.

Round 3: Technical Interview with Hiring Manager

The second technical interview was conducted by the Hiring Manager, who had previously worked as an SDE and therefore had a strong understanding of the technical aspects of the role. The overall structure of the interview was similar to the first technical round, with a coding problem followed by technical and behavioral discussions.

The interview started with a coding problem involving an organizational hierarchy. We were given an

1Employee

I initially recognized the problem as being similar to finding the Lowest Common Ancestor (LCA) in a tree. However, since each employee could have multiple reports, this was effectively an N-ary tree rather than a binary tree. The interviewer asked me why LCA won’t work here, and after a little bit of reasoning I got it.

The interviewer encouraged me to think about the problem from a bottom-up perspective. Based on this hint, I developed a brute-force approach and explained the reasoning behind its O(H) time and O(H) space complexity, where H represents the height of the hierarchy. The interviewer asked me to justify the complexity, and after discussing the approach, he asked me to write the code on the sheet of paper.

Once the initial solution was complete, he asked whether the approach could be optimized further. I took some time to think through the problem while explaining my thought process aloud. The interviewer provided a few hints during the discussion, which helped me move towards a more optimal approach. I eventually arrived at the optimized solution and explained its reasoning and complexity.

The next part of the interview focused on Generative AI and my experience using AI tools. Some of the questions included:

• What Generative AI tools have you used?

• How have you used AI in your internships and projects?

• How do you use Generative AI in your day-to-day life?

• To what extent do you use Generative AI?

• What has your overall experience with AI been?

• How do you use AI while developing software?

The discussion focused more on my practical experience with Generative AI, rather than purely theoretical questions. I discussed how I use AI as a development and productivity tool and how I have incorporated it into my projects and workflow.

Towards the end of the interview, the interviewer shared some feedback with me. I was then given an opportunity to ask questions, and I asked several questions about the role, the team, and his experience at Amazon.

The interview then concluded.

4. Overall Experience and Tips

• Overall Interview Experience: My overall experience was great. Both interviewers were professional, patient, and helpful throughout the process. The interviews felt more like technical discussions than one-sided interrogations. They gave me enough time to think, encouraged me to explain my reasoning, and provided hints when I was stuck. At the same time, they asked meaningful follow-up questions to test whether I genuinely understood my solutions and projects.

• What to prepare? The interview revolves mostly around DSA. So make sure you are able to solve medium level problems from each DSA topic. The most asked categories are : Arrays, Hashing, Heaps, Trees, Graphs.

• Tips for Aspirants: Be thorough with DSA. Striver’s A2Z DSA sheet is enough for Amazon. Make sure you understand problems instead of mugging up because you will be asked follow ups to test your understanding. Be confident, clearly communicate your thoughts, even if you don’t know an answer surely, make sure you are thinking out loud as it lets the interviewer know in which direction you are going.

• Verdict: Selected ✅

Never underestimate your own ability. You are probably capable of much more than you think. I never imagined that I would one day crack Amazon, but here I am. Keep working hard, stay consistent, and trust yourself. You may be closer to your goals than you realize.