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Explain Backend Fundamentals and AI Tooling

ByteDanceBackend Engineer · HR Screen
HardBackend EngineerHR ScreenSoftware Engineering Fundamentals

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This question tests foundational knowledge across systems engineering, database design, version control, and modern AI integration strategies.

Technical Depth Assessment

As a Backend Engineer, you are expected to navigate both traditional distributed system infrastructure and emerging AI-driven workflows. Please provide concise, technical explanations for the following topics:

1. Systems & Networking

  • Explain the fundamental differences between a process and a thread in terms of memory space and context switching overhead.
  • When designing a high-throughput streaming service, under what specific conditions would you prefer UDP over TCP?

2. Database Fundamentals

  • Explain the impact of a B-Tree index on INSERT vs SELECT operations. Why might an over-indexed table degrade performance?
  • Define the difference between a primary key and a unique constraint, and explain when you would choose a surrogate key (like a UUID) over a natural key.

3. Version Control

  • Explain the architectural difference between git merge and git rebase regarding the commit history. In a CI/CD environment, which one is generally preferred for a feature branch and why?

4. AI Tooling & Integration

  • You are building an LLM-powered agent to perform content moderation. How do you distinguish between 'function calling' (tool use) and RAG (Retrieval-Augmented Generation)?
  • When comparing LLMs for a backend production environment, what metrics (beyond accuracy) should be considered to ensure the service remains responsive and cost-effective?

Hints

Hint 1

For processes vs. threads, consider how they handle shared memory and the cost of the OS scheduler switching states.

Hint 2

For databases, remember that indexes are auxiliary data structures that must be updated whenever the underlying data changes.

Hint 3

For AI integration, focus on whether the LLM is fetching external knowledge versus performing an action on an external system via an API.

Follow-up questions

  • How would you handle a scenario where a database index causes a deadlock in a high-concurrency environment?
  • If your AI agent's tool call takes longer than the upstream client's timeout, what architectural pattern would you implement to resolve this?
  • Describe a strategy to implement zero-downtime database schema migrations while maintaining index integrity.