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Anthropic interview notes, page 23 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·Software Engineer·Technical Phone Screen

Jun 2026
Anthropic SWE interview with a performance debugging question. Pretty minimal info to go on but the core problem was interesting enough.
  • You're given profiler samples from a running program. How do you identify the slowest part of the code?

“My first instinct was to talk about flame graphs and where the most CPU time accumulates, but I second-guessed myself halfway through and started rambling about sampling frequency instead.”

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Anthropic·Software Engineer·Technical Phone Screen

Jun 2026
Anthropic software engineering interview where they drop you into an existing codebase and ask you to add a new endpoint while also hunting down pre-existing bugs. More realistic than a whiteboard problem, but also more stressful because there's a lot going on at once.
  • You're given a skeleton API server with existing endpoints, middleware, and a data layer. Add a new endpoint per the provided spec, wire up routing, validation, and proper response codes, and make sure tests are updated.

“The hardest part wasn't adding the endpoint itself.”

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Anthropic·Software Engineer·Onsite - Coding / Algorithms

Jun 2026
Onsite coding round at Anthropic for a software engineer role. The interviewer was completely stone-faced the whole time, barely said a word, and every response I got was just a flat 'ok, good' with zero indication of whether I was on the right track.
  • Design and implement a file system (object-oriented / class-based approach).

“The silence from the interviewer made this so much harder than it needed to be.”

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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 a distributed rate limiter. The question had real depth to it, way more than the typical 'design a rate limiter' you see in prep guides.
  • Design a distributed rate limiter that enforces a per-client request quota globally across a fleet of stateless application servers sitting behind a load balancer.
  • Compare fixed-window, sliding-window-log, sliding-window-counter, and token bucket approaches. Which would you pick to smooth bursts and what is the memory cost of each?
  • If each server falls back to a local limit of N divided by server count during a Redis outage, what breaks when the server count is stale or servers are being added and removed?
  • How would you keep the rate limiter's own latency low when the shared store is healthy, for example through batching, pipelining, or short-TTL local caching of over-limit verdicts?
  • How would you support multiple rate limit tiers and burst allowances within the same mechanism, for example a sustained limit plus a short burst headroom on top?

“I started with the happy path, which was a mistake.”

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Anthropic·Software Engineer·Onsite - Product Sense / Strategy

Jun 2026
Interviewed for a marketing manager role at Anthropic, one question about strategy in a competitive space. Pretty standard for this type of role but it required more depth than I expected going in.
  • Walk me through how you would build a marketing strategy for a new product launching into a highly competitive market like consumer electronics.

“I started with market segmentation and positioning, which felt right, but I think I spent too long on the research phase and didn't get to the actual go-to-market mechanics until they nudged me.”

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Anthropic·Machine Learning Engineer·Onsite - Behavioral / Leadership

Jun 2026
Behavioral round at Anthropic for an ML Engineer role. Just one question but it had a lot of layers to it, more of a conversation than a typical structured interview.
  • Tell me about a time you improved a project outcome by communicating proactively. How did you handle unclear requirements, ask the right questions, negotiate scope, and keep stakeholders aligned? What did you do to make sure communication was actually working?

“This question is way broader than it looks.”

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Anthropic·Software Engineer·Onsite - System Design / Architecture

Jun 2026
System design round at Anthropic for a hardware engineer role. The question was a distributed systems problem which felt a bit out of left field for the role, but I guess they want to know you can think through infrastructure problems end to end.
  • Design a peer-to-peer file distribution system that takes a 10GB file from a single bandwidth-limited source and propagates it to thousands of interconnected hosts, each with constrained upload and download capacity, until every node has the full file.

“Spent the first few minutes just thinking about the naive approach where the source pushes to each host sequentially, which obviously falls apart at scale.”

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Anthropic·Software Engineer·Onsite - System Design / Architecture

Jun 2026
System design round at Anthropic for a software engineering role. One meaty question about building a reference API, and they really pushed on edge cases around resource utilization and scaling.
  • Design a reference API. How would you handle scenarios where the CPU is idle but the GPU is heavily loaded? Walk through your scaling strategy.

“The high-level design part was fine but then they drilled into the CPU/GPU imbalance scenario and I kind of fumbled.”

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Anthropic·Software Engineer·Onsite - Behavioral / Leadership

Jun 2026
Culture and values interview for a software engineering role at Anthropic, focused almost entirely on AI safety thinking. The interviewer pushed hard for concrete evidence behind any claim you made, so vague opinions didn't fly here.
  • What are your views on AI safety, and what critiques do you have of common approaches in the field? Can you back those up with concrete examples or your own testing?
  • Tell me about a time you were convinced someone else was wrong, but ended up significantly changing your own view.
  • How do you think about the trade-off between releasing large AI models and the safety risks that come with that? Should companies like Anthropic be releasing these models at all?
  • What's your take on the Long-Term Benefit Trust as a governance mechanism? Do you think it's actually capable of constraining Anthropic?

“This is where I stumbled.”

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Anthropic·Software Engineer·Technical Phone Screen

Jun 2026
Coding round at Anthropic for a software engineer role, focused entirely on building an LLM-based agent from scratch. You actually write the code, not just talk through it, which I did not fully expect going in.
  • Build a working agent loop that uses an LLM API to solve a given task, including tool definitions, output parsing, and termination logic.
  • What prompting techniques did you use in your agent design, and what are the trade-offs between them?
  • How would you evaluate whether your agent is correct and robust enough for production use?

“This is the whole interview, basically.”

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