On platforms like Zhihu and Reddit, it's common to see misleading advice like "Amazon interviews are easy as long as you grind enough LeetCode." But when you're actually in the hot seat, you quickly realize these interviews test more than algorithms. They evaluate whether you can think and act like an engineer—turning real-world problems into scalable code.
This article walks you through a real Amazon interview experience where CSOAHELP provided full real-time remote support to a candidate. We’ll reveal what’s really behind a seemingly simple “find command clone” task and how our real-time assistance helped the candidate break down the problem, express their thinking, complete the code, and communicate smoothly—securing a pass.
The candidate was a backend engineer from China with several years of experience. Though comfortable with algorithm problems, he often struggled with abstract interface design and system-level questions. Expressing ideas clearly in English—especially for open-ended problems—was another weak spot.
Before the interview, the candidate shared the scheduled time and job role. Our CSOAHELP team prepared a tailored support plan. We analyzed the likely question types based on past Amazon interviews and prepared keyword templates, code skeletons, and real-time hint prompts to be displayed silently on a second screen during the Zoom interview.
The question was:
"Imagine that you need to write code in a high level language like java, that does things similar to the find command. I would like you to focus on 2 uses cases at first.
Find all files over 5 MB somewhere under a directory.
Find all XML files somewhere under a directory.
I would like you to create a library that lets me do this easily. Keep in mind that these are just 2 uses cases and that the library should be flexible."
The candidate was initially a bit flustered, trying to restate the question. We immediately provided a prompt: clarify the requirements and propose a structure—such as using interfaces for filters and building a main class to handle traversal and filtering. He followed our hint and asked, “Can I design a general-purpose file search class where filters like file size or extension can be plugged in via interfaces?”
The interviewer agreed and emphasized that the library should be flexible and easily extensible.
We prompted the next design step: define a FileFilter interface with a boolean matches(File file) method, and then implement SizeFilter and ExtensionFilter. The main FileFinder class should recursively walk the directory tree and apply the filter.
Guided by this structure, the candidate confidently explained the idea. The interviewer nodded and asked him to begin coding.
We showed the code skeleton on the secondary screen so he could follow and type it smoothly:
The interviewer was satisfied with the foundation and asked how the traversal would be implemented. We immediately pushed a suggestion: use recursion and store matching files in a list.
The candidate explained, “I’ll use a recursive method to go through subdirectories and collect files that pass the filter into a result list,” then wrote the next part, guided by our code reference:
Next, the interviewer asked, “How would you support multiple filters? For example, files larger than 5MB AND with .xml extension?”
Before the candidate could hesitate, we provided a structured suggestion: implement a composite filter (AndFilter) that holds a list of FileFilter instances and returns true only if all match.
He quickly typed the following:
The interviewer seemed pleased with his organizational thinking and moved on to increase the difficulty: “If this tool were used in production, how would you improve performance and reliability?”
We updated our suggestion in real time: mention multi-threaded traversal for large directories, proper exception handling, symbolic link loops, logging, testability, and possibly fluent APIs. Recommend choosing two or three to expand on.
Following the prompt, the candidate responded, “I’d switch to using thread pools for concurrent directory traversal to improve speed with large file trees. I’d also include try-catch blocks to handle IO exceptions gracefully, avoiding crashes due to permission errors or symlink loops. Additionally, I’d consider supporting filter chaining through a fluent API to improve usability.”
The interviewer concluded, “Good abstraction. Your interface is clean and future-proof.”
The interview lasted about 50 minutes. With CSOAHELP’s real-time guidance, the candidate handled design, coding, and communication effectively—and was invited to the next round: system design.
This case shows that Amazon interviews aren’t just testing whether you can write recursive functions. They want to see if you can think like an engineer—designing systems that are clean, extensible, and communicable.
And that’s exactly where CSOAHELP’s real-time support makes the difference.
We don’t answer for you. But we ensure that every sentence, every line of code, and every explanation you give is clear, confident, and complete.
Struggle with expressing your ideas? We help you structure your answers. Freeze when coding under pressure? We prep the essential code blocks in advance. Go blank under stress? We’re right there on your second screen, feeding you the keywords and scaffolding to keep you moving.
Top-tier interviews aren’t just about skills—they’re about your ability to perform under pressure. Our service helps you unlock and fully demonstrate the capability you already have.
So if you're preparing for interviews at Amazon, Google, Meta, Apple, or other top companies and don’t want to leave anything to chance, CSOAHELP is your trusted partner. We’re not a cheat service or a grind class—we’re your real-time interview co-pilot, there when it counts most.
经过csoahelp的面试辅助，候选人获取了良好的面试表现。如果您需要面试辅助或面试代面服务，帮助您进入梦想中的大厂，请随时联系我。
If you need more interview support or interview proxy practice, feel free to contact us. We offer comprehensive interview support services to help you successfully land a job at your dream company.
