Katkat

Company

Hebbia interview questions

6 practice questions in the style of Hebbia's interviews, covering ML System Design, System Design, Coding & Algorithms.

Questions6

0 easy4 medium2 hard

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Hebbia interview questions by the numbers

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Katkat has 6 Hebbia interview questions. The largest topics are Coding & Algorithms (50%), ML System Design (33%) and System Design (17%). By difficulty: 67% medium and 33% hard. The most common round is Onsite (67%). Frequent concepts include Logic, RAG, System Design and Agents.

Topics

Difficulty

  • Medium67% · 4
  • Hard33% · 2

Interview rounds

  • Onsite67% · 4
  • Technical Screen33% · 2

Roles

  • Software Engineer83% · 5
  • Machine Learning Engineer17% · 1

Frequent concepts

  • Logic33% · 2
  • RAG33% · 2
  • System Design33% · 2
  • Agents17% · 1
  • Arrays17% · 1
  • Game Theory17% · 1

Showing 1–6 of 6 results

  • Design Hebbia Chat for SEC FilingsMedium

    This problem tests your ability to design a retrieval-augmented generation (RAG) system specialized for financial documents, focusing on multi-agent orchestration, citations, and latency management.

    HebbiaSoftware EngineerML System DesignTechnical Screen
  • Design a Multi-Agent Chat BackendMedium

    This question evaluates a candidate's ability to design scalable, reliable backend architectures that integrate LLMs and multi-agent orchestration, covering distributed systems, streaming responses, conversation context management, tool integrations, observability, and secure handling of sensitive financial data.

    HebbiaSoftware EngineerSystem DesignOnsite
  • Design a Multi-Agent Document Search and Visualization ProductHard

    This problem tests your ability to design a complex multi-agent orchestration system that integrates large-scale document retrieval with reliable citation tracking and a user-facing visualization interface.

    HebbiaMachine Learning EngineerML System DesignOnsite
  • Detect a Winner on a 3x3 Tic-Tac-Toe BoardHard

    This problem tests your ability to efficiently represent board states and implement win-condition logic for a grid-based game.

    HebbiaSoftware EngineerCoding & AlgorithmsOnsite
  • Implement Ultimate Tic-Tac-ToeMedium

    This problem tests your ability to design a state-management system for a nested game board and implement recursive winner-detection logic.

    HebbiaSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Implement a Cache Snapshot PrinterMedium

    This question evaluates understanding of LRU cache semantics, data structures for maintaining recency and eviction, and techniques for serializing or compressing state by grouping identical values while preserving ordering.

    HebbiaSoftware EngineerCoding & AlgorithmsOnsite

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