# Get a Job at Anthropic: Interview Process and Top Questions Aced (formerly Exponent) publishes a public search API over its indexed pages; the guide is at https://www.aced.io/agents/agent-access. Source: https://www.aced.io/blog/anthropic-interview-process Source observed: 2026-11-04T22:21:20.310Z Last checked: 2026-11-04T22:21:20.31+00:00 Indexed: 2026-11-06T17:41:21.435+00:00 --- # Get a Job at Anthropic: Interview Process and Top Questions We created this guide to help you prepare for Anthropic interviews and pursue a job there. It covers Anthropic's company background, reported interview stages, role-specific differences, sample questions, preparation advice, and links to our Anthropic-focused resources. The guide was last updated a month ago when captured and was created with insights from software engineers, machine learning engineers, and research fellows who recently interviewed at Anthropic. ## About Anthropic ### What is Anthropic? Anthropic is an AI safety company founded in 2021 by Dario Amodei, Daniela Amodei, and several former OpenAI researchers. It builds Claude, a large language model used by millions worldwide. Anthropic has reported more than 18.9 million monthly active users of its AI tools and products. ### Where is Anthropic located? Anthropic is headquartered in San Francisco and has offices in New York, Seattle, and London. It grew from roughly 50 employees in 2021 to well over 1,000. Most roles are office-based under a hybrid policy that expects staff to be in one of its offices at least 25% of the time. Relocation support is available. ### Who does Anthropic hire? Anthropic emphasizes intellectual curiosity, safety-mindedness, and careful consideration of technology's implications. Its [careers page](https://www.anthropic.com/careers?ref=exponent-blog.ghost.io) says that direct AI or ML experience is not required for every role and that many current team members began without hands-on experience with these systems. About half of Anthropic's technical staff hold advanced degrees, while many successful colleagues never attended college. Common engineering roles include software engineer, research engineer, machine learning engineer, and research scientist. Anthropic hires fewer [product managers](https://www.aced.io/courses/pm?ref=exponent-blog.ghost.io) than other technology companies of similar size. Its culture and technical direction are discussed on the [Anthropic engineering blog](https://www.anthropic.com/engineering?ref=exponent-blog.ghost.io). ### Anthropic interview resources - [Anthropic Software Engineer Interview Guide](https://www.aced.io/guides/anthropic-software-engineer-interview?ref=exponent-blog.ghost.io) - [Anthropic Machine Learning Engineer Interview Guide](https://www.aced.io/guides/anthropic-machine-learning-engineer-interview?ref=exponent-blog.ghost.io) - [Anthropic Infrastructure SWE Interview Guide](https://www.aced.io/guides/anthropic-infrastructure-software-engineer-interview?ref=exponent-blog.ghost.io) - [Anthropic Interview Questions](https://www.aced.io/questions?company=anthropic&ref=exponent-blog.ghost.io) - [Anthropic Interview Experiences](https://www.aced.io/experiences?company=anthropic&ref=exponent-blog.ghost.io) - [Anthropic Company Hub](https://www.aced.io/companies/anthropic?ref=exponent-blog.ghost.io) ## Anthropic interview process The reported process typically includes: 1. **Recruiter screen(s):** One or two calls about your background, motivation, and compensation expectations. 2. **Technical phone screen:** A 60–90 minute remote coding assessment in a collaborative environment. 3. **Onsite loops:** Two separate interview days covering system design, coding, culture fit, behavioral topics, and a technical project deep dive. The process commonly takes **1 to 4 months** from application to offer. Recruiter communication is reported to be strong, and every interviewer may ask some version of **“Why Anthropic?”** Prepare a specific answer. ### Role-specific differences - **Software engineering:** Practical, real-world coding challenges; see our [software engineering course](https://www.aced.io/courses/software-engineering?ref=exponent-blog.ghost.io). - **Machine learning engineering:** Rounds may focus on MCP tooling, context-window management, and model reliability; see our [machine learning course](https://www.aced.io/courses/ml-engineer?ref=exponent-blog.ghost.io). - **ML and prompt engineering:** Candidates may use Claude Sonnet as a working tool during technical rounds. - **Most other roles, including most SWE positions and the AI Safety Fellowship:** AI-tool use is not permitted during live interviews. ### How hiring decisions work The onsite is divided into two loops on separate days. If you do not pass Loop 1, Loop 2 is cancelled. The first day therefore produces an initial pass/fail decision. The culture-fit round is reported as the most common failure point, rather than the technical rounds. ## Recruiter screen A recruiter screen lasts **15–30 minutes** and covers your background, experience, and interest in Anthropic. Some candidates have two calls: an initial screening call followed by a more senior recruiter's call about compensation and preparation materials. Recruiters may ask for specific details about the platforms and models you have used, the challenges you faced, and why Anthropic specifically rather than AI generally. Compensation may be discussed early through a quoted base-salary range or two compensation bands. Treat numbers discussed at this stage as informational rather than a final offer. Before the onsite, recruiters send blog posts and documents about Anthropic's AI-safety approach. Read them and form your own opinions before the culture-fit rounds. ### Preparation Research Anthropic's products and mission. Explain why this company interests you, not only why AI interests you. Be ready to describe your technical background concretely, including tools and models you have actually used. ## Technical phone screen The technical phone screen is a **60–90 minute** remote assessment in a shared environment such as CodeSignal, Replit, or Google Colab. Problems generally begin simply and become more complex as you progress. The guide describes practical exercises rather than traditional algorithm puzzles. Examples include: - Building a small-site web crawler, then making it multithreaded and filtering its crawled data. - Implementing an in-memory database with features such as TTL (time to live) and advanced querying. - For ML engineering, working on MCP tooling, error diagnosis, or model reliability for long-running tasks. Interviewers may add constraints continuously. They assess reasoning and communication as well as running code. Completing every part is not always expected; explaining your approach clearly when time runs out can still help you advance. Python is the default language. The environment varies by role: - **CodeSignal:** Automated assessments, especially for fellowship positions. - **Replit:** Live coding with an engineer. - **Google Colab:** ML-focused rounds requiring GPU access. Confirm your environment before the interview so configuration problems do not consume interview time. ## Onsite loops The final round consists of two separate loops on different days: - **Loop 1:** Usually system design, coding, and culture fit. - **Loop 2:** Experiences and goals, followed by a technical project deep dive. Each round lasts **55–60 minutes**. If Loop 1 is unsuccessful, Loop 2 is cancelled. Loops may be in person at Anthropic offices or virtual, depending on location and role. Interviewers typically come from one engineering group, such as infrastructure, although they may represent different teams. ### Round types **System design** focuses on LLM infrastructure and distributed systems. Reported prompts include designing batch-inferencing APIs, optimizing GPU use under batching constraints, and distributing large model files across thousands of machines. Interviewers may not have a predetermined correct answer; they want to see how you reason through novel constraints. Use our [system design interview course](https://www.aced.io/courses/system-design-interviews?ref=exponent-blog.ghost.io) for additional practice. **Coding** uses practical problems rather than LeetCode. Examples include analyzing stack-trace profiler samples to find the slowest function, building an image-processing pipeline with unfamiliar libraries, and implementing file deduplication. Interviewers introduce edge cases and failure scenarios during the round. At staff level, candidates are expected to anticipate test cases independently. **Culture fit** has the highest reported failure rate. Two interviewers—one active and one shadowing—ask about ethics, values, and moral conflicts at work, often following up three or four levels deep. Example questions include: - “Tell me about a time you had a moral conflict with the work.” - “What concerns do you have with our mission?” - “How do you decide between delivery speed and security?” **Experiences and goals** is conducted by a manager-level interviewer and covers career trajectory, previous projects, conflict resolution, and the teams in which you thrive. Questions may focus on teams you disliked, strategies you found limiting, and difficult feedback. **Technical project deep dive** requires a presentation about a past project you owned end to end. Candidates have reported using Notion. Two interviewers probe technical decisions, cross-team coordination, and tradeoffs. This round functions more like a [behavioral interview](https://www.aced.io/courses/eng-behavioral?ref=exponent-blog.ghost.io) than a purely technical interview. ## Anthropic interview questions These are examples of real questions reported in Anthropic interviews. Practice further with our [Anthropic interview question bank](https://www.aced.io/questions?company=anthropic&ref=exponent-blog.ghost.io). ### Coding - Build a web crawler with multithreading. - Determine the longest-running function from stack-trace samples. - Read files and eliminate duplicates. - Justify a list of words within a given width. - Serialize and deserialize a list of strings. - Implement an in-memory database with progressively complex features. ### System design - Design a batch-inferencing API. - Batch queries and optimize GPU usage. - Design a scalable token-generation service handling up to **100,000 requests per second**. - Distribute files across thousands of machines with bandwidth constraints. - Design a file-cache system. ### Behavioral and culture fit - Tell me about a time you had a moral conflict with the work. Who did you talk to, and what changed your mind? - What concerns do you have with Anthropic's mission or direction? - How do you balance delivery speed with security concerns? - Tell me about a time you received negative feedback and how you handled it. - Describe a time you disagreed with your manager and later changed your mind. - What are the ethical risks of deploying agentic AI systems in high-stakes environments? - Why do you want to work at Anthropic? - Tell me about a time you built something that went against your values. - What is your honest critique of Anthropic's direction? ### Machine learning - If your model exposed sensitive data from its training set, what would you do next? - How do you adjust the creativity of generative AI models? - Define hallucinations in LLMs. - Design an agentic AI system that can autonomously adapt to new tasks. - How do you keep users' data safe and private when building AI systems? ## Tips for getting hired at Anthropic 1. **Read the safety materials from your recruiter.** Culture-fit interviewers may ask what you understood and what opinions you formed. 2. **Prepare for difficult culture-fit discussions.** Practice discussing moral conflicts, ethical pressure from leadership, personal values, pushback, and ethical concerns. Expect three or four levels of follow-up. 3. **Study the team's actual work.** Research the engineering group's challenges, such as inference optimization, safety tooling, and agent infrastructure. The prompt may have no known solution. 4. **Treat early compensation discussion as non-final.** Quoted bands or base ranges are informational anchors, not offers. 5. **Follow Anthropic employees on X.** Their posts may help you develop specific answers to “Why Anthropic?” ## Frequently asked questions ### Does Anthropic hire new graduates? Anthropic does not currently offer traditional internships. It runs an **AI Safety Fellowship**, a **six-month paid** position closer to full-time work than an internship. Fellows work on research projects with senior-researcher mentorship, and strong performers may convert to full-time positions. ### Can I reapply after rejection? Anthropic asks rejected candidates to wait **12 months** before reapplying. Earlier applications may be considered when something meaningful has changed, such as directly relevant experience or significant research. ### Does Anthropic provide interview feedback? Candidates report that Anthropic does not provide feedback after rejection. You can contact your recruiter with a specific hypothesis about the problem round; this may produce more detail than a general feedback request. ### Is the process virtual? Recruiter screens and the technical phone screen are always remote. Onsite loops may be in person or virtual depending on location and role. Candidates far from the Bay Area, New York, Seattle, or London have completed full loops remotely. ### Is AI experience required? No. Anthropic's [careers page](https://www.anthropic.com/careers?ref=exponent-blog.ghost.io) says many roles do not require an LLM, AI, or ML background, and that many current team members began without hands-on experience in these systems. The guide also says familiarity with AI coding assistants is practically necessary for technical rounds, even without professional AI-system experience. ## Prepare with Aced - Review recently asked [Anthropic interview questions](https://www.aced.io/questions?company=anthropic&ref=exponent-blog.ghost.io) and candidate answers. - Practice with our [mock interview tools](https://www.aced.io/practice?ref=exponent-blog.ghost.io). - Get role-specific [Anthropic interview guides](https://www.aced.io/companies/anthropic?ref=exponent-blog.ghost.io). - [Create a free Aced account](https://www.aced.io/signup?src=blog). We are Aced, formerly Exponent. We provide tech interview preparation through interview guides, insider tips, courses, practice, coaching, resume review, salary negotiation, interview questions, and interview experiences. Browse [Anthropic interview questions](https://www.aced.io/questions?company=anthropic&src=blog). ## Related blog posts - [Get a Job at ByteDance: Interview Process and Top Questions](https://www.aced.io/blog/bytedance-interview-process) - [Get a Job at Anduril: Interview Process and Top Questions](https://www.aced.io/blog/anduril-interview-process) - [Get a Job at xAI: Interview Process and Top Questions](https://www.aced.io/blog/xai-interview-process) - [Get a Job at Snowflake: Interview Process and Top Questions](https://www.aced.io/blog/snowflake-interview-process) --- [Read this page’s summary](https://www.aced.io/agents/api/public/v1/page-tldr?url=https%3A%2F%2Fwww.aced.io%2Fblog%2Fanthropic-interview-process&trace=t_679ff9ab98f3) ## Ask a follow-up about this page Need a more specific answer? Ask the exact question you have. It returns a fresh, cited answer from Aced (formerly Exponent)’s knowledge base. No account or API key required. 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