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Anthropic interview notes, page 2 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·Product Manager·Onsite - Product Sense / Strategy

Apr 2026
PM interview at Anthropic, just one question about launching to an existing user base. Pretty lean in terms of what I can share but it stuck with me.
  • How would you go about launching a new product to our existing user base?

“I spent too long on segmentation and not enough on the actual rollout mechanics.”

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Anthropic·Software Engineer·Technical Phone Screen

Apr 2026
Interviewed for a SWE role at Anthropic, got asked about recent AI advancements. Pretty fitting given where the company sits.
  • What recent developments in AI have caught your attention?

“Felt like a warm-up but I overthought it.”

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Anthropic·Software Engineer·Onsite - Behavioral / Leadership

Apr 2026
Behavioral round at Anthropic focused on cross-functional dynamics. Just the one question but they really sat with my answer and asked a bunch of follow-ups I wasn't ready for.
  • Tell me about a time you had a conflict during a cross-functional collaboration, such as with a PM, designer, data team, or another engineering team. What was the conflict, how did you handle the communication, and what came out of it?

“I had a decent story ready about a disagreement with a PM over scope, but the follow-ups are where I started to fumble.”

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Anthropic·Software Engineer·Technical Phone Screen

Apr 2026
Coding round at Anthropic for a software engineer role, one question but it had enough depth to keep me busy for a while. The edge case handling was where things got tricky.
  • Implement a transfer function and an accept-transfer function for accounts. When a transfer is initiated, the source account should hold the funds. Also handle the case where a timeout occurs and a subsequent deposit should cancel the pending transfer.

“Got the basic transfer and accept parts down fine, but that timeout edge case wrecked me.”

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Anthropic·Machine Learning Engineer·Technical Phone Screen

Apr 2026
Interviewed for an ML Engineer role at Anthropic and got a coding problem that looked deceptively simple at first glance. The follow-up is what really got me thinking.
  • Given a sequence of function calls, convert them into a timeline of start and end events, where each call generates a corresponding start event and end event. Output the full event sequence in order.
  • Follow-up: modify your solution so that only runs of the same function call that meet or exceed a given threshold count are emitted as events. Runs shorter than the threshold should be merged or ignored.

“Seemed straightforward until I started thinking about ordering edge cases.”

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Anthropic·Software Engineer·Technical Phone Screen

Apr 2026
This was a later-stage coding round for a recipe service system, building on top of prior levels. The focus was on adding order cancellation and user history tracking, which sounds straightforward but the edge cases pile up fast.
  • Implement a cancel_order function that handles edge cases like cancelling an already-cancelled order, a completed order, or an order that doesn't exist at all.
  • Implement a track_record function that returns a user's full order history including timestamps and statuses, and handle the case where the user has no orders yet.

“I jumped straight into the happy path and the interviewer just sat there quietly until I realized I hadn't said a word about completed orders.”

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Anthropic·Product Manager·Onsite - Product Sense / Strategy

Apr 2026
Interviewed for a PM role at Anthropic and got hit with a pretty heavy ethics question about agentic AI. Not a typical product sense round, more like a policy and risk discussion dressed up as a PM interview.
  • What are the ethical risks of deploying agentic AI systems in high-stakes environments?

“I wasn't ready for how broad this was.”

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Anthropic·Software Engineer·Recruiter / HR Screen

Apr 2026
HR screen for a software engineer role at Anthropic. Six questions, mix of motivation and light technical risk stuff, and the recruiter actually sent reading materials beforehand which made prep pretty straightforward. Passed through to the next round.
  • Why do you want to work at Anthropic?
  • What do you see as the biggest risks and biggest benefits of advanced AI?
  • What stood out to you about Anthropic's Responsible Scaling Policy?
  • What is your current seniority level at your current company?
  • Tell me about a project you led from start to finish.
  • How long did that project take?

“Standard opener but Anthropic's mission makes it feel more loaded than usual.”

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Anthropic·Machine Learning Engineer·Technical Phone Screen

Apr 2026
Interviewed for an ML engineer role at Anthropic. One question but it was a heavy one, the kind that makes you realize how much you haven't thought about certain failure modes.
  • If you found out your model was leaking sensitive information from its training data, what steps would you take?

“I knew this was about more than just 'retrain the model' but I fumbled the ordering a bit.”

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Anthropic·Software Engineer·Onsite - System Design / Architecture

Apr 2026
System design round at Anthropic for a software engineering role. The whole thing was a web crawler question that started simple and kept escalating into distributed systems territory. Came away feeling like I held my own but definitely left some things on the table.
  • Design a web crawler, starting from a single-machine implementation and then scaling it to multiple servers. Cover the shared work queue, URL deduplication across nodes, per-domain rate limiting, failure handling and retry logic, and horizontal scalability. You don't need to fully implement the distributed version, just explain the architecture and the trade-offs.

“I started with the single-machine version which felt fine, a queue of URLs, a visited set, fetch and parse loop.”

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