Amazon In the North American market, the competition is super fierce, and the success rate of Amazon SDE positions in 2025 is only 2-4%! Don't panic, although Amazon VO is strict, but if you are well-prepared, you will be able to come out on top! In this article, we will give you the linen interview experience and practical advice to help you rush to the offer with confidence!
Amazon VO Preparation
After the resume is approved, it will enter the first round of formal interviews - the line manager interview, which lasts 45-60 minutes. Detailed communication will be conducted based on the resume's past experiences, mainly asking basic behavior questions around the resume. After passing one round, a loop interview time will be scheduled, and the group will provide a time slot selection.
Amazon virtual onsite (VO) has 4–5 rounds and lasts about 4 hours, testing coding, system design, and behavioral performance. For NG roles, it’s usually 3 rounds, and New Grad interviews don’t include a system design round. For technical positions, you should grind LeetCode medium to hard problems (arrays, trees, dynamic programming), practice with HackerRank and Chime (Amazon’s VO tool), and get used to explaining your thinking while coding. For system design, understand high-concurrency scenarios such as order or recommendation systems, and study DynamoDB and SQS. For behavioral questions, prepare 3–5 STAR stories tightly aligned with Amazon’s 16 Leadership Principles, such as “Customer Obsession.”
Amazon VO process
Resume Screening：After your resume passes screening, HR will have a brief conversation with you to assess your fit for the role. They may ask why you chose Amazon and why you applied for this position, and have you briefly introduce your past work experience and previous compensation. HR will also give a short overview of the role’s background and explain the next steps in the interview process.
OA：On the HackerRank platform. The test lasts 90 minutes and includes two algorithm problems; for SDE roles, there is also.work simulationand work style.
Technical phone screen: One round, 45 minutes long, using Amazon Chime for whiteboard coding, requiring you to solve an algorithm problem.
VO Loop：There are a total of 4–5 rounds. Two rounds are coding interviews that assess algorithms and coding ability; one round is a system design interview that evaluates system architecture and design skills; and 1–2 rounds are behavioral interviews based on the Leadership Principles. A Bar Raiser may participate during the process to ensure interview quality.
Algorithm + System Design + Behavioral Questions
This interview consisted of three main questions covering algorithms, system design, and Amazon style behavioral questions. I've included my own solutions or reference answers for each question for students preparing for tech positions.
Round 1
BQ + Coding: This round feels more focused on the behavioral part. They started with questions around the Leadership Principles, mainly emphasizing Customer Obsession and Ownership.
BQ：
- Why Amazon?
- Tell me about a time you failed at work. What did you learn from it?
- Tell me about a challenge you faced. What was your role & the outcome?
Coding：This round featured a binary tree traversal problem (an original LeetCode question or a very similar variant).
The core of the problem was: given the root node `root` of a binary tree, implement a zigzag level-order traversal. This is essentially the original LeetCode 103, *Binary Tree Zigzag Level Order Traversal*. When the interviewer asked for my approach, my first instinct was inorder traversal. The moment I realized inorder was incorrect, I corrected myself and said it should be postorder traversal. The interviewer gave a wry smile and noted that my initial inorder idea could barely be a starting point if I adapted it to process by levels, but the more direct standard solution is to use a queue for BFS.
Round 2
Round 2 was the Bar Raiser (LP + Coding). The so-called Bar Raiser round really was tougher. The LP focus was on Learn and Be Curious and Deliver Results.
Coding:The interviewer gave a course-dependency validation problem, asking me to design a function to check whether the course catalog of an e-learning platform is valid. My approach was to use a two-dimensional checking algorithm to detect missing courses. Then I handled cycle detection (topological sort) by building a graph and an indegree map. I designed the graph direction as “prerequisite course → dependent course.” Finally, I combined these checks for overall validation. The focus was on the logic of code design and maintainability. The amount of code was fairly large, and I felt this round was the key one for differentiating candidates.
Round 3
Round 3 mainly focuses on LP + system design. The LP emphasis is on Earn Trust and Have Backbone. The system design question requires you to think about scalability, reliability, and high availability. This round tests whether you can design a complete and well-rounded system in a complex scenario.
System Design Question: Amazon Recommendation System
Problem Description:
Design an e-commerce recommender system that is required to support billions of users and products with low latency and high relevance. For example, when users browse cell phones, to be able to recommend the corresponding accessories or similar phones.
My solution to the problem is as follows:
Architecture section:
- User behavior data stored in DynamoDB
- Product indexes are built with ElasticSearch
- Asynchronous processing of recommended tasks with SQS
- Top Picks Results Cached with Redis
Process Design:
User sends a request → API Gateway receives it → Recommendation service calls ES to get candidate products → query user's historical behavior → return recommendation list after comprehensive scoring
Summary of key points:
- For the recommendation algorithm layer I used collaborative filtering (item-based)
- System scalability by database sharding
- Latency control relies on caching and asynchronous queues
Time complexity: about O(log n) for queries, O(1) for cache hits
Round 4
Round 4 is mainly BQ + Coding.
1. Tell me about a time you failed/The biggest mistake you made.
2. Take a risk, or do not have much time, to make a decision/ Tellme about a time when you had to work on a project with unclear responsibilities.
3. Most challenging/proudest project/Tell me a time you solved a conplex problem
OOD：Design a loan website that finds suitable loans for users based on their preferences. Once a user clicks a loan link, they will be redirected to an external URL. Key points: API design and database design. I also mentioned using an algorithm/hash-sharding approach for data partitioning, specifically using SHA-1. Follow up:How to handle a large number of requests?
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