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Anthropic interview notes, page 15 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·Onsite - System Design / Architecture

May 2026
Brutal system design round at Anthropic for a software engineer role. One question, but it basically covered every dimension of distributed systems I've ever studied, and then some I hadn't.
  • Design a production-ready file deduplication service. Cover the full architecture including ingestion, chunking, indexing, storage, and metadata layers. Walk through your API design, read and write workflows, and explain how you'd handle consistency, idempotency, fault isolation, failure recovery, and disaster recovery. Also address backfills and compaction/GC, index sharding and rebalancing, deployment and rollback strategies, schema migration, monitoring and SLOs, capacity planning, cost controls, privacy and compliance requirements, and how you'd protect production workloads from degradation.

“I started with chunking and content-addressable storage because that felt like the core insight, hash the chunks, deduplicate by hash, done.”

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Anthropic·Machine Learning Engineer·Technical Phone Screen

May 2026
Anthropic ML engineer interview with a pretty gnarly coding question about converting sampling profiler output into a visualization-friendly trace of start/end events. The problem had a lot of edge cases to reason through and required both clean implementation and a discussion of design decisions.
  • Given a list of sampling profiler samples (each with a timestamp and a call stack), implement a function that converts them into a sequence of start/end trace events suitable for visualization. Use the longest common prefix between consecutive stacks to determine which frames ended and which started. Also handle the first sample, the last sample, duplicate function names at different depths, empty stacks, equal timestamps, and optionally a synthetic root frame. Provide time and space complexity.

“This one took me a while to even parse.”

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Anthropic·Software Engineer·Technical Phone Screen

May 2026
Anthropic hardware engineer interview that was essentially a library-wrangling exercise. They gave you real image files across a bunch of folders and asked you to build a pipeline that reads per-image instruction files and applies transformations in order. No algorithm design, just figure out the right library and make it work.
  • Build an image-processing pipeline that reads per-image instruction files and applies ordered transformations (rotate, invert, crop, convert, etc.) across large sets of images in multiple folders of varying sizes.

“They gave actual files, not mocks, which I wasn't expecting.”

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Anthropic·Software Engineer·Onsite - Behavioral / Leadership

May 2026
Behavioral round at Anthropic for a software engineer role. Just one question but they really dug into it.
  • Walk me through the most challenging project you've worked on. What made it hard, what was your specific contribution, and what came out of it?

“They weren't just asking for a story.”

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Anthropic·Software Engineer·Technical Phone Screen

May 2026
Interviewed for a software engineer role at Anthropic and got a mix of graph traversal, file system parsing, and a spicy LRU cache extension. The last one had more layers than I expected going in.
  • Implement a web crawler that starts from a given URL and only visits pages within the same hostname.
  • Given a list of file paths and their contents, find all groups of duplicate files based on content.
  • Extend a standard LRU cache implementation to work as a decorator that handles variable-length positional and keyword arguments, and also support serialization and deserialization for persistence.

“Straightforward BFS/DFS problem once you realize hostname filtering is the whole point.”

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Anthropic·Software Engineer·Technical Phone Screen

May 2026
Coding round for a Software Engineer role at Anthropic. Just one question on file deduplication, nothing else to report.
  • Design or implement a file deduplication system.

“Not much context shared about how this went.”

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Anthropic·Software Engineer·Onsite - System Design / Architecture

May 2026
Did a system design round at Anthropic for a software engineer role. Classic prompt, but I fumbled the time management pretty badly and never got to the parts that probably matter most.
  • Design a one-on-one chat system.

“Sank too much time into requirements and API surface area.”

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Anthropic·Software Engineer·Technical Phone Screen

May 2026
Coding round for a Software Engineer role at Anthropic. The problem was an in-memory key-value store with nested transaction support, which sounds manageable until you actually think through rollback semantics across multiple transaction layers.
  • Implement an in-memory key-value store supporting SET, GET, DELETE, and COUNT operations, plus nested transactions with COMMIT and ROLLBACK semantics.

“The basic CRUD part is trivial.”

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Anthropic·Software Engineer·Technical Phone Screen

May 2026
Anthropic SWE interview with a classic LRU cache design question, but they pushed way further than the usual 'just use a hashmap and doubly linked list' answer. Spent a good chunk of time on the extensions and edge cases.
  • Design an in-memory key-value store with fixed capacity N that evicts the least recently used entry when full. Support get and put in amortized O(1) time and O(N) space. Walk through your data structures, pseudocode for both operations, and how you'd handle updates to existing keys, N=0, thread safety, and extensions for a peek operation and delete.

“The core LRU part I knew cold.”

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Anthropic·Software Engineer·Onsite - Behavioral / Leadership

May 2026
Anthropic's non-technical loop for SWEs has two rounds: a culture/values interview and a hiring manager deep dive with a project presentation. No coding, but don't let that fool you into under-preparing. The scrutiny on ownership and values alignment is intense.
  • Why do you specifically want to work at Anthropic, and what is your personal view on AI safety?
  • Tell me about a time you had a strong disagreement with someone at work. What was the conflict, how did you handle it, and what happened to the relationship afterward?
  • Describe a situation where two values you genuinely held were in conflict with each other. How did you decide what to do?
  • Walk me through a complex project end to end: your specific role, the risks you saw coming vs. the ones that surprised you, the impact, and how you influenced the roadmap.
  • In the project deep dive, walk me through an alternative design you seriously considered and rejected. What would have happened if you had gone that route instead?
  • Give a roughly 20-minute presentation on a project you led, covering the problem, your approach, key decisions, results, and what you'd do differently. Then field detailed questions on it.
  • Where do you think the current consensus on AI safety is wrong, or where would you push back on mainstream thinking in the field?
  • How have you mentored someone on your team, and what lasting impact did it have on their growth?

“This one is deceptively hard.”

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