Anthropic Interview Questions (May 2026)

39 questions · 51 experiences · 2 discussions · 1p3a_oj (46) · 1p3a (33) · InterviewDB (9) · Reddit (2) · LeetCode (2)

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Anthropic Technical Interview (55 min CodeSignal) – Anyone done this before?

Reddit SWE
Feb 2026 Question

Design a 1-to-1 Chat System

1p3a SWE Los Angeles
Feb 2026 Question

Task Management System (Online Assessment)

1p3a SWE Los Angeles
Jan 2026 Question

Banking System (Online Assessment)

1p3a SWE San Francisco
Nov 2025 Question

Web Crawler

1p3a SWE Los Angeles
Nov 2025 Question

Employee Management System (Online Assessment)

1p3a SWE
Nov 2025 Question

Inference API System Design

1p3a SWE Paris
Nov 2025 Question

Prompt Playground System Design

1p3a SWE USA
Nov 2025 Question

Recipe Manager (Online Assessment)

1p3a SWE San Francisco
Nov 2025 Question

Distributed Model Deployment System Design

1p3a SWE San Francisco
Oct 2025 Question

Deduplicate Files

1p3a SWE
Oct 2025 Question

Tokenize (Python)

1p3a SWE
Oct 2025 Question

LLM Request Batching API System Design

1p3a SWE USA
Oct 2025 Question

Converting Stack Samples to Trace Events

1p3a SWE Paris
Oct 2025 Question

Distributed Mode and Median

1p3a SWE Remote
Oct 2025 Question

In-memory Database (Online Assessment)

1p3a SWE
Oct 2025 Question

Anthropic Onsite Interview: In-Memory Cache Extension Coding Challenge

1p3a SWE
Oct 2025 Question

Interview Question

LeetCode SWE
Mar 2025 Question

Multi-threaded Web Crawler with URL De-duplication

1p3a_oj Data Eng
Question

Web Crawler with Asyncio

1p3a_oj SWE
Question

LRU Cache Extension

1p3a_oj SWE
Question

Efficient Model Deployment in a Cluster

1p3a_oj SWE
Question

Python Class and Data Structures

1p3a_oj SWE
Question

In-Memory Database

1p3a_oj SWE
Question

Route Multiple Prompt Calls to Multiple GPT Servers Using a Hash Table

1p3a_oj SWE
Question
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Anthropic Interview Process Overview

The Anthropic interview process typically includes a recruiter screen, one to two technical phone screens, and a 4-6 round on-site or virtual on-site loop. Each round serves a distinct calibration purpose: coding rounds measure correctness, code quality, and complexity reasoning; system design rounds measure architectural judgment at the appropriate level; behavioral rounds measure ownership, leadership scope, and collaboration. Reports tagged on LeakCode from 2024-2026 show Anthropic runs a calibrated process consistent with industry norms for companies of its tier.

Difficulty calibration: Anthropic coding rounds typically run medium difficulty with follow-up depth as the senior discriminator. System design rounds expect production-grade trade-off articulation at L4+ levels. Behavioral rounds expect quantified outcomes ("reduced p99 latency from 800ms to 120ms") rather than vague impact claims. The candidates who advance consistently demonstrate clear thinking out loud rather than perfect final answers.

How To Use Anthropic Question Reports

Real candidate-reported interview questions are a calibration tool, not a memorization target. Anthropic updates its question pool every 2-4 months; memorizing exact problems risks misleading you when the interviewer uses a variant. The high-leverage approach: identify the patterns that appear repeatedly in Anthropic reports, practice those patterns on similar (not identical) problems, and use the reports to understand the interviewer's typical follow-up depth.

Filter the questions above by round type, difficulty, and recency. Focus first on reports from the past 6-12 months; older reports may reference questions that have since rotated out of Anthropic's pool. Reports tagged with quantified difficulty and explicit round type are higher-signal than reports without those tags. The metadata filters help you build a focused study plan in 1-2 hours rather than 8-10 hours of unstructured browsing.

Common Anthropic Interview Mistakes

Reports tagged "no hire" at Anthropic consistently surface a few patterns: jumping into code without clarifying requirements, coding silently for extended periods, missing edge cases (empty input, single element, large input, overflow), producing working code the candidate cannot refactor when probed, and behavioral stories that use "we" instead of "I" diluting individual signal. Strong candidates explicitly avoid these patterns by following a consistent round template.

The single most predictive failure mode in recent reports: not asking clarifying questions. Interviewers are explicitly trained to weight this dimension. Strong candidates ask 3-5 clarifying questions even on problems that look obvious; weak candidates dive into implementation immediately. Strong candidates also verbalize their approach before writing code; weak candidates code in silence and lose the communication dimension of the round's calibration.