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Software Engineer Interview Questions
Practice 9403 coding, system design and machine learning questions from 546 companies, sorted by role, topic and interview round. Every question has step-by-step hints, a code runner that supports 8 languages and an AI mentor; members also get the full solution walkthrough.
- 9403
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- 11
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Showing 271–300 of 2336 results
- AnthropicMediumSoftware EngineerDiscuss Ethical Judgment and Unwanted Work
Tests a candidate's self-awareness, ethical responsibility, and ability to navigate professional disagreements or undesirable tasks while maintaining team trust and high standards.
Behavioral & LeadershipOnsitebehavioralethicsleadership - AnthropicMediumSoftware EngineerDiscuss culture and mission alignment
This question evaluates alignment with organizational mission, ethical and safety judgment, decision-making under ambiguity, receptiveness to blunt feedback, collaboration style, and practices for sustaining engineering quality—core behavioral and leadership competencies for software engineers.
Behavioral & LeadershipOnsite - AnthropicMediumSoftware EngineerDistribute 500 GB of Model Weights to 1,000 GPU Workers: Lower Bound and Design
Copy 500 GB of model weights to 100 to 1,000 GPU workers whose 10 Gbps links are shared between upload and download. Derive the lower bound on distribution time, evolve a naive fan-out into a chunked peer-to-peer design, and handle stragglers, failures and cutover. It tests bandwidth reasoning and large-scale distribution design.
System DesignOnsite - AnthropicHardSoftware EngineerEstimate FFN Compute, Memory, and Sharding Communication
Estimate standard FFN FLOPs, parameter and activation bytes, and sharding communication, then compare compute, HBM, and network limits with explicit layout assumptions.
ML System DesignOnsite - AnthropicHardSoftware EngineerEstimate VRAM and compare model parallelism
This question tests the ability to calculate memory overhead for transformer model parameters and activation buffers, while evaluating the architectural trade-offs between tensor and pipeline parallelism for large-scale training.
ML System DesignOnsiteDistributed SystemsGPU ArchitectureTransformer Training - AnthropicMediumSoftware EngineerExplain Anthropic motivation and leadership stories
This question evaluates leadership, ethical reasoning, cultural fit, communication, and project ownership, targeting Behavioral & Leadership competencies for a software engineer role.
Behavioral & LeadershipOnsite - AnthropicHardSoftware EngineerExplain How You Resolved a Professional Conflict
Explain a professional conflict through fair opposing views, shared criteria, a concrete resolution process, personal adjustments, and follow-through.
Behavioral & LeadershipOnsite - AnthropicMediumSoftware EngineerExplain Ownership of a Project Business Metric
Tests an engineer's ability to define, instrument, and own business or platform metrics, ensuring alignment with technical outcomes while actively managing guardrails and proxy risks.
Behavioral & LeadershipOnsiteBehavioralMetrics & TelemetryEngineering Leadership - AnthropicHardSoftware EngineerExplain Your AI Safety Values
Assesses how an engineer conceptualizes AI safety and risk, translates ethical principles into concrete engineering trade-offs, and navigates organizational friction or ambiguity when escalating potential harms.
Behavioral & LeadershipOnsiteAI SafetyBehavioralRisk Management - AnthropicMediumSoftware EngineerExplain career goals and cultural alignment
Explain career goals and cultural alignment evaluates behavioral evidence, ownership, communication, trade-offs, and measurable outcomes in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Behavioral & LeadershipOnsite - AnthropicHardSoftware EngineerExplain projects and handle AI-safety conflicts
This question evaluates leadership, technical ownership, communication, trade-off analysis, ethical reasoning, and judgment on AI safety by asking candidates to describe projects and defend value-driven decisions.
Behavioral & LeadershipOnsite - AnthropicHardSoftware EngineerExplain the Most Complex Situation You Have Handled
Explain a complex professional situation through conflicting constraints, personal responsibility, evidence-based decisions, coordination, and lessons from the outcome.
Behavioral & LeadershipOnsite - AnthropicMediumSoftware EngineerFind Duplicate Files
This question evaluates a candidate's skills in file-system traversal, content deduplication strategies, hashing, large-file I/O handling, concurrency, and robustness to errors and file changes during scans.
Coding & AlgorithmsOnsite - AnthropicHardSoftware EngineerFind Duplicate Files by Content
This question evaluates the ability to parse file-system-style input, group files by identical content, and manage deduplication using appropriate data structures and algorithms.
Coding & AlgorithmsOnsite - AnthropicMediumSoftware EngineerFind Duplicate Files by Content in a Directory Tree and Explain CPU vs I/O Costs
Walk a directory tree and report every group of files with identical contents, printing nothing when there are no duplicates. It tests staged filtering by size and hashes, streaming reads of large files, link and error handling, and reasoning about whether the job is CPU-bound or I/O-bound.
Software Engineering FundamentalsOnsite - AnthropicHardSoftware EngineerFind a Distributed Mode Efficiently
Design an exact distributed mode-finding algorithm across partitioned workers that minimizes network I/O, prevents hotspotting, handles deterministic tie-breaking, and contrasts with approximate streaming sketches.
System DesignOnsitedistributed-systemssystem-designalgorithms - AnthropicMediumSoftware EngineerFind and remove duplicate files
This question evaluates the ability to design scalable file deduplication algorithms, specifically testing knowledge of hashing strategies, collision handling, memory and I/O optimization, handling very large files, incremental/resumable operation, and complexity and trade-off analysis.
Coding & AlgorithmsOnsite - AnthropicMediumSoftware EngineerFind the Slowest Function from Profiler Events
This question evaluates the ability to interpret time-ordered profiler event logs, compute inclusive and exclusive function runtimes, reason about call-stack semantics, and recognize anomalies such as recursion, cycles, missing end events, or non-returning functions.
Coding & AlgorithmsOnsite - AnthropicMediumSoftware EngineerFix a Buggy LRU Cache, Then Make It Durable with a Write-Ahead Log
Debug a flawed least-recently-used cache by finding each bug with a reproducing call sequence and fixing it, then make the cache durable across crashes with a write-ahead log and snapshots. It tests careful code reading, constant-time LRU design, crash-consistent persistence and recovery.
Software Engineering FundamentalsOnsite - AnthropicHardSoftware EngineerFunction-Call LRU Cache: Argument Key Generation and Crash Recovery from a Log
A Python exercise that builds an LRU cache for memoizing function calls. Part one asks how to generate a reliable cache key from a function and its arguments; part two adds crash recovery through an append-only log file, testing record framing, durability, torn writes and replay of the cache state.
Software Engineering FundamentalsOnsite - AnthropicHardSoftware EngineerGuide and override compiler optimizations
This question evaluates a candidate's competency in low-level performance engineering and compiler optimization techniques—covering pragmas, intrinsics, manual code transformations, profiling and correctness verification—within the System Design and compiler-aware optimization domain.
System DesignOnsite - AnthropicMediumSoftware EngineerHiring-Manager Behavioral Round: Impact, Conflict, Cross-Functional Work, and Influencing Without Authority
Tests a candidate's ability to drive technical initiatives across teams, navigate cross-functional disagreements, and exert leadership without formal management authority.
Behavioral & LeadershipOnsiteBehavioralLeadershipCross-Functional - AnthropicHardSoftware EngineerHow do you design an A/B experiment?
This problem tests your ability to design a rigorous A/B experiment for a consumer-facing AI product, focusing on identifying interference, selecting appropriate metrics, and addressing statistical validity.
Analytics & ExperimentationOnsiteA/B TestingExperiment DesignMetrics - AnthropicHardSoftware EngineerHow do you lead under risk and uncertainty?
This question evaluates leadership competencies—risk assessment, stakeholder management, conflict resolution, and decision-making under uncertainty in engineering contexts.
Behavioral & LeadershipOnsite - AnthropicHardSoftware EngineerHow do you review a design document?
This question assesses a candidate's ability to critically evaluate technical design documentation by identifying architectural risks, scalability bottlenecks, and gaps in operational planning.
Software Engineering FundamentalsOnsiteSystem DesignCode ReviewReliability - AnthropicMediumSoftware EngineerHow to Handle the First-Round Interview at an AI Safety Lab
A structured prompt for the earliest conversation in the loop at a lab whose mission is AI safety, where most of the time goes to why you want to work there specifically and how you think about the risks of the technology, not resume review. Tests depth, specificity, and whether your safety views connect to real experience.
Behavioral & LeadershipOnsitebehavioralmotivationai-safety - AnthropicMediumSoftware EngineerHow to stream a large file to 1000 hosts fastest
Design a high-throughput distribution system to broadcast a large file (e.g., 100 GB model checkpoint) to 1,000 cluster hosts in minimum time, analyzing network bottlenecks and replication topologies.
System DesignOnsitedistributed-systemssystem-designnetworking - AnthropicMediumSoftware EngineerImplement Parallel Image Processing
This question evaluates competency in concurrent and parallel processing, practical image manipulation with Python libraries (Pillow), resource management for memory and file I/O, robust error handling, and performance measurement.
Coding & AlgorithmsOnsite - AnthropicHardSoftware EngineerImplement Persistent Memoization LRU Cache
This problem tests your ability to design a decorator that memoizes function results using an LRU policy while ensuring the cache survives process restarts via disk serialization.
Coding & AlgorithmsOnsitePythonLRU CacheDecorator - AnthropicMediumSoftware EngineerImplement Python LRU cache with args and persistence
This question evaluates a candidate's ability to design and implement an LRU cache in Python that supports variable-length positional and keyword arguments with canonical, deterministic hashing for semantically equivalent calls and O(1) get/put via a hash map plus a doubly linked list; it falls under the Coding & Algorithms domain and primarily tests practical implementation skills, API robustness, hashing/equality subtleties, and algorithmic complexity guarantees. The persistence follow-up evaluates understanding of serialization and storage design — on-disk formats, versioning, and atomic write strategies — and compares trade-offs between binary pickle and JSON-based serialization in terms of security, compatibility, and performance, reflecting both conceptual design and practical system-level considerations.
Coding & AlgorithmsOnsite
Anthropic