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Design an internal interest-matching platform

Last updated: Mar 29, 2026

Quick Overview

This question evaluates system design skills for building an internal interest-matching platform, including real-time scalable architecture, data modeling, API design, search and recommendation systems, messaging, and privacy/access controls.

  • hard
  • Palantir
  • System Design
  • Software Engineer

Design an internal interest-matching platform

Company: Palantir

Role: Software Engineer

Category: System Design

Difficulty: hard

Interview Round: Technical Screen

Design a system for a company to connect employees who share similar interests. Specify key features (profile creation, interest tagging, discovery, messaging), data model and storage choices, APIs, and the matching/recommendation approach. Discuss privacy and access controls for internal-only visibility, ranking signals, and how to handle cold start. Provide a high-level architecture (services, databases/search indices, cache, event/queue) and describe how it scales to tens of thousands of employees with near real-time updates as interests change. Outline monitoring/metrics and abuse prevention.

Quick Answer: This question evaluates system design skills for building an internal interest-matching platform, including real-time scalable architecture, data modeling, API design, search and recommendation systems, messaging, and privacy/access controls.

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Palantir logo
Palantir
Jul 15, 2025, 12:00 AM
Software Engineer
Technical Screen
System Design
42
0

System Design Prompt: Internal Employee Interest Matching Platform

Context

Design an internal-only platform that connects employees with similar interests to foster collaboration, mentorship, and community. Assume a typical enterprise environment with SSO, an HR directory, and tens of thousands of employees. The system should provide near real-time updates when interests change.

Requirements

  • Features
    1. Profile creation and editing
    2. Interest tagging (free text with normalization and a suggested taxonomy)
    3. Discovery and search (by tags, location, team, etc.)
    4. Matching/recommendations (who should I connect with?)
    5. Messaging (1:1 and small group)
  • Data model and storage choices
  • APIs (profile, interests, discovery, recommendations, messaging)
  • Matching and ranking approach (signals, algorithm)
  • Privacy and access controls (internal-only visibility, role/attribute-based)
  • Cold start strategy
  • High-level architecture (services, databases/search indices, cache, event/queue)
  • Scaling plan to tens of thousands of employees with near real-time updates
  • Monitoring/metrics and abuse prevention

Solution

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