Openai·Software Engineer·Onsite - Coding / Algorithms·Senior

SeniorPrefer not to say

Apr 2026

Summary

OpenAI SWE coding round, one big design-and-implement question that took the whole session. The problem sounds straightforward until you realize extensibility is the whole point and they're watching how you structure things, not just whether it runs.

Questions Asked (1)

Design and implement an extensible chat application that supports multiple bots and multiple channels. Each channel should have independent message history and bot state. Adding new bot types should not require changes to core logic.

System DesignTechnical Trade-offsAPI & Integrations

Author's notes

This one ate the entire interview.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and scale, then propose a layered architecture with a core message router and channel manager, using a plugin-based bot interface for extensibility. Walk through data models for channels, messages, and bot state, and discuss trade-offs around storage, concurrency, and API design.

Pro tip: Emphasize that new bot types should be added via configuration or dynamic loading without redeploying core services, and mention how you'd test extensibility with a mock bot.

1. Clarify Requirements and Scale

Ask about expected number of channels, bots, message throughput, and persistence needs to scope the design appropriately.

2. Define Core Components and Interfaces

Outline a channel manager, message router, and bot interface (e.g., handleMessage, getState) that decouples core logic from bot implementations.

3. Design Data Models and Storage

Specify schemas for channels, messages, and bot state, and choose storage (e.g., relational DB for history, key-value for bot state) with isolation per channel.

4. Address Extensibility and Integration

Explain how new bots are registered (e.g., via plugin registry, config file, or dynamic loading) and how they receive messages without core changes.

5. Discuss Trade-offs and Scalability

Cover trade-offs like synchronous vs. asynchronous message processing, consistency vs. availability, and scaling strategies (sharding, queues).

Key Points to Mention

Plugin architecture with a well-defined bot interface (e.g., abstract class or interface) to allow new bot types without modifying core.
Channel isolation: each channel has its own message history and bot state, possibly using separate partitions or namespaces.
Message routing: a central router that dispatches messages to the appropriate bots based on channel subscriptions.
Persistence: use of databases (SQL/NoSQL) for message history and bot state, with considerations for consistency and scalability.
Concurrency: handling simultaneous messages and bot state updates, possibly with locks or optimistic concurrency.
API design: REST or WebSocket endpoints for clients to send/receive messages, and for bots to register and receive events.

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