Anthropic s SDE hiring process has attracted a lot of attention recently. As one of the hottest companies in the AI space right now, their interview style is quite different from traditional tech companies. Many candidates initially assume it will be the usual combination of algorithm practice and system design interviews. However, after actually going through the process, it becomes clear that Anthropic places much greater emphasis on practical engineering ability, code quality, and your understanding of AI safety.
The whole process is not particularly long, but each round is very targeted. If you prepare in the wrong direction, it can easily be brushed off midway. The complete process is sorted out below for preparation. Claude Ask classmates from relevant teams for reference.
Timeline
Generally speaking, it takes about 2–4 weeks from the first round to the final result.
A typical process is:
- Initial Screening
- Technical Phone Screen
- Online Coding Challenge/OA
- Hiring Manager Interview
- Virtual Onsite (4 rounds)
Some teams will put OA before Phone Screen, and the overall order will change slightly, but the core inspection modules are basically the same.
Initial Screening（30min）
Background and motivation communication
The first round was Recruiter Screening, and the overall atmosphere was relatively relaxed. The main thing is to understand the candidate's background and motivation for applying.
Usually we talk about:
- Previous SDE/Backend/Infrastructure project experience
- Do you have experience in distributed systems or service development?
- Work authorization
- Long term career planning
This round will basically not involve technical issues, but is more like a background matching confirmation process.
Culture Fit preliminary judgment
Recruiters usually also introduce the company's mission, such as Anthropic's research direction in AI security. Compared with many companies simply pursuing model capabilities, they emphasize the safety and explainability of AI.
If you understand the relevant content of Constitutional AI in advance, it will be obviously easier to build consensus during this round of communication.
Technical Phone Screen（45min）
Coding: LLM scene engineering questions
Although this round is Coding, it is not a traditional algorithm question, but a scenario question that is closer to large model engineering.
A more common question type is to implement an LLM request scheduling system, such as designing an efficient token batching mechanism. The system needs to process multiple inference requests and reasonably merge them into the same batch to improve GPU inference efficiency.
Candidates need to complete:
- Data structure design
- Batching scheduling logic implementation
- Time complexity and space complexity analysis
This type of question is more like a small engineering system than a simple algorithm question.
Basic Q&A: LLM Engineering Cognition
After coding, a few basic questions are usually discussed to confirm the candidate's understanding of the large model system.
For example:
- What is the main performance bottleneck of LLM inference?
- The role of KV cache in the inference phase
- How to improve inference throughput
The depth of the problem won't be particularly extreme, but it can be easily seen if you have no experience with large model systems.
Coding Challenge/OA（90min）
CodeSignal system simulation questions
Anthropic OA is usually in CodeSignal Completed on. Unlike many companies’ online written tests, it is not a typical LeetCode algorithm question, but more like a complete small system implementation task.
The most common type of topic is banking system simulation. Candidates need to implement a simple account system from scratch and gradually expand the functionality. The questions usually require the realization of functions such as creating accounts, deposits and withdrawals, transfers between accounts, querying transaction records, and implementing cashback logic under certain rules. The overall code amount will be much larger than that of ordinary algorithm questions.
Difficulty: Requirements progress layer by layer
The real difficulty of this type of question is not the algorithm, but the gradual increase in demand. The question may only ask you to implement the most basic account system at the beginning. After you finish writing, the next question will ask you to support transaction record query. In the future, cashback rules may be added, and complex functions such as transaction rollback (reversal of transactions) may even be required.
If the code structure is not designed properly at the beginning, for example, the coupling between classes is too high or the state management is chaotic, it will become very difficult to change every time a function is added later. This is why many people usually only brush LeetCode Candidates will be less comfortable with this type of questions.
Anthropic pays more attention to the quality of engineering code in this round, such as whether the class design is clear, whether the module is easy to expand, whether exception handling is complete, and the overall readability of the code. If the code structure is clear, you can usually get good ratings even if all the functions are not completed.
Hiring Manager Interview (1h)
Code Review Dig Deeper
This round is usually led by the Hiring Manager, and its format is different from traditional coding interviews and more like a real engineering discussion. The interviewer usually gives a piece of code, asks the candidate to conduct a Code Review, and explains possible problems with the code.
Common tasks include finding potential bugs, identifying concurrency-related issues, analyzing performance bottlenecks, and explaining the purpose of this code in a real system. In some cases, the interviewer will continue to ask how you will optimize this code or the overall architecture if the system scale is expanded ten times or the traffic suddenly increases.
This round mainly examines the candidate’s engineering experience and systems thinking ability. Rather than simply writing algorithms, the interviewer is more concerned about whether you can read complex code, discover hidden problems, and propose reasonable improvement plans.
VO, four wheels
The final round is the Virtual Onsite, which typically involves four consecutive interviews for a total duration of approximately four hours. The overall rhythm is relatively compact, and the focus of each round of inspection is also different.
Coding Interview (1h)
This round is still coding, but the questions are usually closer to real business logic rather than particularly tricky algorithm questions. Interviewers would rather see how the candidate organizes code, handles state, and considers boundary conditions.
Common inspection contents include data structure design, status management, and handling of various abnormal scenarios. The overall difficulty of the questions will not be particularly extreme, but if the code structure is confusing or boundary conditions are not considered, the score will usually not be too high.
System Design（1h）
System Design This round usually revolves around Claude Related business scenarios unfold. The interviewer may ask you to design a chat system that supports large-scale user conversations, or discuss how to implement token counting and billing logic, and how to maintain system stability under high concurrent inference requests.
Discussions often involve issues such as API design, data storage solutions, caching strategies, service splitting, and system scalability. This round focuses more on overall architectural thinking rather than specific code implementation.
Second Coding（1h）
In the third round of coding, questions are usually designed based on the candidate’s position. If you are applying for Infrastructure-related positions, the questions may focus on concurrent processing, task scheduling, or resource management. If it is the Fullstack direction, it is more likely to involve API logic implementation or data processing flow.
The overall idea is similar to the first round of coding, but it is more in line with the actual work content of the position.
Behavioral Interview (1h)
The final round is the Behavioral Interview, which is also a very distinctive part of the Anthropic interview. Instead of just asking traditional behavioral questions, interviewers will often discuss some social issues related to AI.
For example, AI ethical issues, data privacy protection, the impact of AI on the job market, and the importance of AI Safety in future technological development. When answering these questions, it is best to express your views clearly and give logical and complete reasoning rather than simply giving vague answers.
Interview preparation supplement
Picture Anthropic In this kind of AI company interview, many people are actually stuck not with algorithms, but with engineering questions and time pressure. For example, OA's system simulation questions, VO's business coding, or HM's Code Review. If you have never done similar types of questions before, it is easy to get stuck on site.
So, many students will learn about interview assistance in advance when preparing. To put it simply, during the OA or VO process, someone will help with real-time thinking reminders. If you are currently preparing for an SDE interview at an AI company or a large factory, you can do it regardless of whether it is OA or VO. Contact us .
