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Review AI Platform And Software Fundamentals

EquinixSoftware Engineer · Technical Screen
MediumSoftware EngineerTechnical ScreenSoftware Engineering Fundamentals

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This problem tests foundational knowledge in software architecture, AI system design, and data structures by requiring the candidate to explain the trade-offs in building a RAG-based document retrieval system.

The Problem: AI Knowledge Base Design

You are tasked with designing a backend service that supports a Retrieval-Augmented Generation (RAG) platform. The system ingests large PDF documents, chunks them, and stores them in a way that allows a Large Language Model (LLM) to retrieve relevant snippets to answer user queries.

Part 1: Data Engineering and Indexing

Explain how you would design an ETL (Extract, Transform, Load) pipeline to process incoming documents. Specifically:

  1. How would you handle document chunking to ensure semantic context is maintained?
  2. What is the role of an embedding model and a vector database in this architecture?

Part 2: System Architecture and SOLID

Suppose you need to build an 'Evaluator' component that grades the quality of the LLM responses. How would you apply the Dependency Inversion Principle (from SOLID) to ensure that your evaluator can support multiple grading strategies (e.g., semantic similarity vs. keyword-based grading) without modifying the main retrieval service?

Part 3: Algorithmic Fundamentals

During query retrieval, your system maintains a list of the top-k most relevant document chunks. If these chunks are stored in a linked list, what is the time complexity of inserting a new chunk while keeping the list sorted by relevance? If you were to optimize this, what data structure would you choose and why?

Hints

Hint 1

Consider how overlapping windows during chunking might preserve context compared to fixed-size character splits.

Hint 2

The Dependency Inversion Principle suggests that high-level modules should depend on abstractions rather than low-level implementations; define an 'EvaluatorInterface'.

Hint 3

Linked list insertion into a sorted structure is O(n), whereas a Min-Heap or a balanced BST would provide significantly better performance for maintaining top-k elements.

Follow-up questions

  • How would you handle real-time streaming updates to the vector database if a document is deleted while the system is serving queries?
  • What are the trade-offs between using a standard SQL database for metadata vs. a specialized vector database for the embeddings?
  • If the 'Evaluator' process becomes a bottleneck, how would you horizontally scale the system while ensuring consistency?