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

SeniorPrefer not to say
Apr 2026

Summary

Did a system design round at OpenAI for a software engineer role. The whole thing was one deep problem about binary serialization for a key-value store, which sounds narrow but ended up covering a lot of ground fast.

Questions Asked (1)

Q1

Design and implement a binary serialization format for an in-memory key-value store. Keys are UTF-8 strings, values can be int64, float64, bool, string, or nested maps. Your format needs a magic header, version field, type tags, length prefixes, endianness convention, and checksums. Implement encode and decode in O(n) time. Then discuss the tradeoffs versus JSON or MessagePack.

System DesignTechnical Trade-offsAlgorithms & Data Structures
Author's notes

This was the whole interview, basically.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then design a binary format with a fixed header and type-tagged, length-prefixed values, ensuring O(n) encode/decode. Implement the encoder/decoder, and finally compare tradeoffs with JSON and MessagePack, highlighting performance, size, and schema evolution.

Pro tip: Mention that you would use a recursive descent parser for nested maps and include a checksum like CRC32 for integrity, but note that checksums add overhead and may be optional for trusted environments.

1. Clarify requirements and constraints

Ask about expected data sizes, performance needs, schema evolution, and whether the format must be human-readable. Confirm that O(n) time is required and discuss memory constraints.

2. Design the binary format

Define a fixed header with magic bytes, version, and flags. Choose big-endian for network order. Assign type tags for each value type and use length prefixes for strings and maps.

3. Implement encode and decode

Write recursive functions that traverse the map, writing type tags and values. For decode, read the header, validate magic and version, then recursively reconstruct the map. Ensure O(n) by processing each byte once.

4. Add checksums and error handling

Compute a checksum (e.g., CRC32) over the payload and include it in the header. On decode, verify the checksum and handle malformed data gracefully.

5. Discuss tradeoffs

Compare with JSON (human-readable, larger, slower) and MessagePack (compact, fast, but less schema flexibility). Highlight when to choose each based on performance, size, and interoperability.

Key Points to Mention

  • Magic header and version field for format identification and evolution
  • Type tags and length prefixes for self-describing data
  • Endianness convention (e.g., big-endian) for cross-platform compatibility
  • Checksum (e.g., CRC32) for data integrity
  • O(n) time complexity by single-pass encoding/decoding
  • Tradeoffs: JSON is human-readable but verbose; MessagePack is compact but lacks schema; custom binary offers performance and control

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