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Anthropic interview notes, page 21 of 32

Mid-sized

Most of these Anthropic write-ups come from Software Engineers (277), then Machine Learning Engineers (31) and Product Managers (10). The most reported rounds are the technical phone screen (129), the system design round (86), the behavioral / leadership round (45) and the hiring manager screen (17).

319 interview notes · updated Sep 2026

Anthropic·Machine Learning Engineer·Technical Phone Screen

Jun 2026
Interviewed for an ML engineer role at Anthropic and got hit with a pretty meaty question about hallucination mitigation in production generative AI systems. Not a lot of small talk, they went straight into the technical stuff.
  • If you deployed a generative AI model to real users and it started hallucinating, how would you handle that?

“This is the kind of question where you think you know what to say and then realize mid-answer you're just listing buzzwords.”

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Anthropic·Software Engineer·Online Assessment (OA)

Jun 2026
Anthropic's CodeSignal pipeline for what I'd call a backend/chat systems role has multiple levels, and by level 4 the problem isn't new anymore, it's the same ChatBox Service from earlier levels but now they care about performance. Time and memory limits get tight and your naive solution from level 1 just won't cut it.
  • Given your earlier ChatBox Service implementation, optimize it to meet strict time and memory constraints when handling large-scale input.

“This is where the earlier levels come back to bite you.”

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Anthropic·Software Engineer·Onsite - Behavioral / Leadership

Jun 2026
Behavioral round at Anthropic for a SWE role. One question but it hit different given the company.
  • Describe a situation where you were asked to build something that went against your personal values.

“This question stings a little more when Anthropic is the one asking it.”

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Anthropic·Software Engineer·Technical Phone Screen

Jun 2026
Coding round at Anthropic for a software engineer role, focused on web crawler implementation. They pushed for a multithreaded version after the basic solution, which is where things got interesting.
  • Implement a web crawler that starts from a given URL and visits all reachable pages sharing the same hostname. You have access to an API that returns all URLs found on a given page. Walk through both a single-threaded and a multithreaded solution.

“The single-threaded BFS part was fine, queue plus visited set, pretty standard.”

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Anthropic·Software Engineer·Hiring Manager Screen

Jun 2026
Hiring manager round at Anthropic for a software engineering role. The interviewer ran pretty cold the whole time and it was hard to get a read on what they actually wanted. Felt like I was talking into a void for 40+ minutes.
  • Walk me through a technically complex project you've worked on.
  • How have you influenced roadmap decisions at your current or previous company?
  • Describe how you've mentored or developed other engineers on your team.

“This took up a big chunk of the conversation.”

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Anthropic·Software Engineer·Onsite - System Design / Architecture

Jun 2026
System design round at Anthropic for a software engineer role, focused entirely on building an inference API service for a large model. The interviewer pushed hard on implementation specifics, not just high-level architecture, which caught me a bit off guard.
  • Design an inference API service that serves a large model (like an LLM or vision model) behind a request/response interface. Walk through API design, request batching, scheduling, autoscaling, model loading, GPU vs CPU trade-offs, monitoring, and SLOs.

“I started with the API surface and worked outward, which felt natural, but I underestimated how deep they wanted to go on the GPU execution side.”

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Anthropic·Software Engineer·Hiring Manager Screen

Jun 2026
Behavioral screen for a software engineer role at Anthropic. Pretty standard resume walkthrough plus a 'why Anthropic' question, nothing technically deep but it felt more personal than most recruiter calls I've had.
  • Walk me through your resume and work experience. What's a project you're most proud of or found most challenging, and what was your specific role in it?
  • Why do you want to work at Anthropic specifically? What draws you to the mission or research direction?

“I rambled a bit here.”

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Anthropic·Software Engineer·Onsite - System Design / Architecture

Jun 2026
System design round at Anthropic for a software engineering role. The whole interview was basically one deep problem about duplicate file detection, and they kept pulling on threads until I ran out of answers.
  • Design a system to detect and optionally remove duplicate files in a directory tree that may not fit in memory. Cover your hashing strategy, how you handle very large files, memory and I/O constraints, collision handling, and how you'd make it incremental and resumable.

“I started with the obvious: group by file size first to avoid hashing everything, then do a partial hash on the first chunk, then full hash only for collisions.”

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Anthropic·Product Manager·Recruiter / HR Screen

Jun 2026
Screened for a PM role at Anthropic, pretty much just one question about my AI background and that was the gist of it.
  • What draws you to AI and why does it interest you?

“Pretty standard opener but I fumbled it a bit.”

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Anthropic·Software Engineer·Onsite - System Design / Architecture

Jun 2026
System design round at Anthropic for a software engineer role, centered entirely on one massive distributed systems problem. The question had a lot of moving parts and the hints they embedded made it clear they wanted you to think carefully before jumping to solutions.
  • Design a system to distribute large ML model weight files to thousands of GPU inference workers across multiple regions, with staged rollout, integrity verification, access control, fast rollback, and minimal serving downtime.
  • Estimate the total bytes moved per release and explain how that number should drive your choice of distribution mechanism.
  • Walk through the safe activation flow on a worker: how do you separate downloading new weights from actually serving them, and what do you keep around for rollback?
  • How does a freshly restarted worker determine which model version it should be running, and what goes wrong if it just picks the newest artifact it finds in storage?
  • A region's cache goes cold right as a large release is ramping there. How do you prevent the origin from getting crushed, and how do you bound egress?
  • A canary rollout of v5 is in progress when an emergency rollback to v3 is triggered. A worker is mid-download of v5 shards. How does it resolve the conflict?
  • The new version passes all shard checksums and infra health metrics look green, but output quality has silently degraded. How does the rollout system catch this before full fleet exposure?
  • How would you extend the design so that two model versions sharing most shards (like a LoRA adapter on a shared base) avoid re-transferring and re-storing the common shards?

“This is one of those questions where the scope is so wide you can spend 45 minutes and still feel like you only scratched the surface.”

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