Anthropic Software Engineer Interview Guide

Anthropic's Software Engineer pipeline usually opens with a recruiter conversation about background and motivation, often followed by a 90-minute CodeSignal-style assessment with up to four levels that ask you to build a small working system rather than solve classic algorithm puzzles. Candidates have described an in-memory database, a banking app, and a task management system with priorities and dependencies. The bar leans toward production quality: one candidate was asked to implement an LRU cache from scratch with a doubly linked list and hashmap, with thread safety and error handling in mind.

Live technical screens lean on practical, concurrency-flavored coding. More than one candidate was asked to build or extend a web crawler, with interviewers pushing on concurrency, timeouts, redirects, and relative versus absolute URLs rather than pure optimality. Another candidate's phone screen centered on Python fundamentals and async behavior.

Candidates who reach the full loop report a mix of coding, system design, and fit conversations. The standout design prompt was an inference API for serving large language models, covering batching strategy, GPU memory management, request queuing, streaming, and KV cache handling. Another candidate faced an LLM-related design problem that required no prior LLM experience. In that round, stating assumptions clearly and driving the conversation mattered most. One candidate was also asked how they operate in a fast-paced, high-intensity environment. Later stages can include reference checks, and communication afterward has sometimes stretched to nearly two weeks. Reported loops range from a single design-focused screen to a phone screen plus four further rounds, so treat the exact stage count as variable by track and level.