Openai·Software Engineer·Onsite - System Design / Architecture·Senior

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Jun 2026

Summary

System design round at OpenAI for a software engineer role, focused entirely on designing a cloud-hosted remote IDE from scratch. The scope was massive and I felt the time pressure pretty hard toward the end.

Questions Asked (1)

Design a cloud-hosted remote IDE similar to GitHub Codespaces or Replit. Walk through the full system including workspace isolation, code editing, language tooling, terminal access, file sync, port forwarding, snapshotting, and cost-efficient scaling.

System DesignTechnical Trade-offsAPI & Integrations

Author's notes

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and scale, then present a high-level architecture before diving into each component. Focus on trade-offs and justify your choices, especially around isolation, scaling, and cost.

Pro tip: Emphasize the importance of cold-start latency and cost per user; propose a tiered storage and compute strategy to balance performance and cost.

1. Clarify Requirements and Scale

Ask about expected user count, concurrency, supported languages, and budget constraints. Define non-functional requirements like latency, isolation level, and persistence.

2. High-Level Architecture

Outline the main components: frontend (editor), backend services (workspace manager, file sync, terminal proxy), and infrastructure (container orchestration, storage, networking).

3. Deep Dive into Key Components

Explain workspace isolation (containers/VMs), code editing (Monaco/VS Code), language tooling (LSP), terminal access (WebSocket), file sync (inotify + CRDT), port forwarding (reverse proxy), and snapshotting (persistent volumes).

4. Scaling and Cost Efficiency

Discuss autoscaling, resource limits, spot instances, and tiered storage. Address cold-start mitigation and idle workspace hibernation.

5. Trade-offs and Alternatives

Compare container vs VM isolation, centralized vs distributed file systems, and synchronous vs asynchronous sync. Justify choices based on requirements.

Key Points to Mention

Workspace isolation using containers (Docker) or lightweight VMs (Firecracker) for security and resource efficiency.
Language Server Protocol (LSP) for code intelligence and tooling integration.
Efficient file synchronization with conflict resolution (e.g., CRDTs) and low-latency updates.
Port forwarding via reverse proxies (e.g., Traefik) with authentication and TLS termination.
Snapshotting using persistent volumes (e.g., EBS) and incremental backups for fast restore.
Cost optimization through autoscaling, spot instances, and hibernation of idle workspaces.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.