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System Design interview questions

1311 System Design questions from 230 companies, with hints, runnable code and solution walkthroughs.

Questions1311

60 easy819 medium432 hard

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System Design interview questions by the numbers

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Katkat has 1,311 System Design interview questions from 230 companies; the most come from OpenAI (8%), Meta (5%) and Amazon (4%). By difficulty: 5% easy, 62% medium and 33% hard. The most common round is Onsite (55%). Frequent concepts include System Design, Distributed Systems, Scalability and Caching.

Companies (230)

Difficulty

  • Easy5% · 60
  • Medium62% · 819
  • Hard33% · 432

Interview rounds

  • Onsite55% · 721
  • Technical Screen39% · 517
  • Online Assessment3% · 38
  • Other2% · 21
  • HR Screen1% · 13

Roles

  • Software Engineer91% · 1189
  • Machine Learning Engineer2% · 31
  • Data Engineer2% · 26
  • Backend Engineer2% · 25
  • Frontend Engineer1% · 19

Frequent concepts

  • System Design31% · 400
  • Distributed Systems24% · 316
  • Scalability15% · 196
  • Caching7% · 95
  • Concurrency7% · 91
  • system-design6% · 83

Showing 901–930 of 1311 results

  • This question evaluates a candidate's competency in designing multi-tenant conversational AI services with reusable, versioned presets, covering API design, data modeling, session state and context-window management, scalability, multi-tenant isolation, privacy, and observability.

    OpenAISoftware EngineerSystem DesignTechnical Screen
  • This question tests the ability to design a distributed calendar system focusing on synchronization, conflict resolution for overlapping time slots, and efficient storage of recurring events.

    OpenAISoftware EngineerSystem DesignTechnical Screen
  • An OpenAI software-engineering system-design screen asking you to design a scalable, multi-tenant CI/CD platform. It spans Git/event intake, YAML workflow parsing into a job DAG, fair scheduling and runner isolation, live log and status streaming, per-tenant quotas and billing, observability, audit logging, disaster recovery, and zero-downtime deploys.

    OpenAISoftware EngineerSystem DesignTechnical Screen
  • This question evaluates skills in large-scale distributed systems architecture, real-time messaging and presence, data modeling for multi-tenant platforms, security and compliance features, and operational concerns like observability and cost efficiency.

    OpenAISoftware EngineerSystem DesignTechnical Screen
  • This question tests the ability to design a high-consistency payment processing system that handles asynchronous state transitions, authorization holds, and batch settlement workflows.

    OpenAISoftware EngineerSystem DesignTechnical Screen
  • This question evaluates skills in designing real-time surge pricing systems, assessing competencies in machine learning modeling, control and pricing logic, data engineering, operational robustness, explainability, and monitoring within the System Design domain.

    OpenAIMachine Learning EngineerSystem DesignOnsite
  • This question evaluates a candidate's competency in designing multi-tenant distributed systems with strong isolation and sandboxing, runtime lifecycle management, real-time output/log streaming, data persistence, autoscaling, and observability.

    OpenAISoftware EngineerSystem DesignOnsite
  • Design a scalable payment system evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    OpenAISoftware EngineerSystem DesignTechnical Screen
  • This question evaluates a candidate's ability to design a real-time, low-latency search autocomplete system, exercising competencies in architecture, indexing and serving, ranking and personalization, typo-tolerance, multilingual support, abuse prevention and privacy-aware data handling; it is categorized under System Design and emphasizes practical application with architectural-level conceptual reasoning. It is commonly asked to assess how candidates balance stringent latency and scalability requirements with personalization and trending signals, robustness to input errors and multiple languages, and metrics-driven trade-offs across caching, ranking and monitoring.

    OpenAIMachine Learning EngineerSystem DesignOnsite
  • This question tests the ability to design a scalable, low-latency, real-time messaging system, focusing on message ordering, delivery guarantees, and high-concurrency state management.

    OpenAISoftware EngineerSystem DesignTechnical Screen
  • Design a GPU job scheduler for a text-to-video generation service where each task runs on a single GPU and users share capacity through fair queueing. It tests job store design, fairness by GPU time rather than task count, leases and retries, and failure handling across workers, GPUs and the scheduler.

    OpenAISoftware EngineerSystem DesignOnsite
  • This problem tests your ability to design a scalable, low-latency document editor that integrates real-time AI streaming responses into a persistent, collaborative text environment.

    OpenAISoftware EngineerSystem DesignTechnical Screen
  • This question tests the ability to design a high-latency, asynchronous job-processing pipeline with a focus on fault tolerance, job state management, and reliable resource handling.

    OpenAISoftware EngineerSystem DesignOnsite
  • This question assesses the ability to architect a high-scale feed system by balancing pre-computation (push model) versus on-demand computation (pull model) to minimize latency for social media users.

    OpenAISoftware EngineerSystem DesignTechnical Screen
  • This question tests your ability to design a distributed payment architecture that supports asynchronous transactions and reliable reconciliation between offline Point-of-Sale (POS) terminals and a centralized ledger.

    OpenAISoftware EngineerSystem DesignTechnical Screen
  • Design a platform that gives ML engineers on-demand, GPU-backed notebook workspaces they can create, connect to, pause, and resume, covering lifecycle and API design, provisioning latency, persistent storage, and idle-cost control.

    OpenAISoftware EngineerSystem DesignTechnical Screen
  • Design an online chess platform: match players of similar Elo rating quickly, deliver moves in real time over WebSocket connections, and enforce fair game clocks despite network latency and disconnections. It tests matchmaking, stateful real-time architecture, server-authoritative timing and failover.

    OpenAISoftware EngineerSystem DesignOnsite
  • This problem tests the ability to design a real-time, stateful gaming system, focusing on concurrency control, low-latency communication, and fault tolerance.

    OpenAISoftware EngineerSystem DesignOnsite
  • System design question about an online devbox service that gives engineers cloud development environments they can create, connect to, stop and resume. It tests lifecycle and API design, fast provisioning, persistent workspace storage, connection routing, isolation of user code, idle cost control and failure handling.

    OpenAISoftware EngineerSystem DesignTechnical Screen
  • Design an online devbox with authenticated workspace access, isolated code execution, persistent project files, reliable stop/resume, and controlled startup costs.

    OpenAISoftware EngineerSystem DesignTechnical Screen
  • Design an online chess service where two remote players play live games, every move is validated and delivered to the opponent immediately, and results are recorded. It tests authoritative game state, real-time transport, fair clocks, move ordering, recovery of games in progress after failures, and scaling to many concurrent games and spectators.

    OpenAISoftware EngineerSystem DesignOnsite
  • This question tests your ability to design a distributed system that manages stateful, long-running compute resources while ensuring isolation, high availability, and secure remote access.

    OpenAISoftware EngineerSystem DesignOnsite
  • This problem tests the ability to architect a high-performance, in-memory key-value store, focusing on concurrency control, data structures, and durability guarantees.

    OpenAISoftware EngineerSystem DesignTechnical Screen
  • Design an in-memory key-value database evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    OpenAISoftware EngineerSystem DesignTechnical Screen
  • Design a card payment system for coffee shops where purchases are authorized at the counter, tips are added afterwards, and transactions settle in a nightly batch. The discussion centers on scaling nightly settlement, along with idempotent APIs, failure handling and reconciliation against processor reports.

    OpenAISoftware EngineerSystem DesignOnsite
  • This question evaluates understanding of distributed-systems concepts such as vector clocks, partial orders, concurrency control and idempotency, plus practical competencies in data structures and algorithms for efficient per-user state management and correctness under concurrent operations.

    OpenAISoftware EngineerSystem DesignTechnical Screen
  • This question evaluates a candidate's ability to design and reason about in-memory data storage, indexing, query planning, and the underlying data structures and algorithms for insert and query operations.

    OpenAISoftware EngineerSystem DesignTechnical Screen
  • Design a monitoring system for power grid field devices that report their status over an unreliable public internet. It tests store-and-forward reporting, idempotent ingestion of late and duplicate data, telling silent devices from failed ones, alerting, and security for critical infrastructure.

    OpenAISoftware EngineerSystem DesignOnsite
  • Design a high-throughput, fault-tolerant GPU job scheduler tailored for large-scale text-to-video generation workloads under sustained compute contention. The problem evaluates distributed resource allocation, multi-node gang scheduling, fairness guarantees, and preemption mechanics.

    OpenAISoftware EngineerSystem DesignTechnical Screen
  • This question evaluates proficiency in distributed system design, covering scalability, availability, durability, data modeling, geospatial indexing, event-driven delivery, API design, fault tolerance, security, and operational monitoring for high-throughput backend services.

    OpenAISoftware EngineerSystem DesignOnsite

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