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Design a Real-Time Suggestions Service

Last updated: Mar 29, 2026

Quick Overview

This question evaluates a candidate's ability to design low-latency, globally scalable real-time typeahead/autocomplete systems, assessing competencies in distributed systems, indexing and search data structures, ranking and personalization, caching, streaming and batch data pipelines, telemetry, and fault-tolerant architecture.

  • hard
  • SoFi
  • System Design
  • Software Engineer

Design a Real-Time Suggestions Service

Company: SoFi

Role: Software Engineer

Category: System Design

Difficulty: hard

Interview Round: Onsite

Design a system that provides real-time typeahead/autocomplete suggestions as users type. Cover API design and request/response schemas, data modeling and indexing (e.g., prefix trees or inverted indexes), ranking signals and personalization, latency targets (e.g., <100 ms P 95), caching layers, scalability, freshness and backfill pipelines, A/B experimentation hooks, and failure handling.

Quick Answer: This question evaluates a candidate's ability to design low-latency, globally scalable real-time typeahead/autocomplete systems, assessing competencies in distributed systems, indexing and search data structures, ranking and personalization, caching, streaming and batch data pipelines, telemetry, and fault-tolerant architecture.

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SoFi logo
SoFi
Jul 16, 2025, 12:00 AM
Software Engineer
Onsite
System Design
10
0

System Design: Real-Time Typeahead/Autocomplete

Context

Design a real-time typeahead/autocomplete service for a consumer-facing web and mobile application. Users see suggestion updates on each keystroke. Assume global traffic, multiple locales, and both anonymous and signed-in users.

Requirements

Design the system and cover:

  1. API design and request/response schemas
  2. Data modeling and indexing (e.g., prefix trees, FST, inverted indexes)
  3. Ranking signals and personalization
  4. Latency targets and budgets (e.g., P95 < 100 ms)
  5. Caching layers (edge, in-memory, distributed)
  6. Scalability and capacity planning
  7. Freshness and backfill pipelines (batch + streaming)
  8. A/B experimentation hooks and telemetry
  9. Failure handling and graceful degradation

State assumptions where needed and justify trade-offs.

Solution

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