System Design Interview Questions 2026
System design interviews are critical for senior AI roles. These questions cover scalable AI architectures, vector search systems, ML pipelines, and distributed systems.
How would you design a scalable RAG system that handles 10,000 queries per minute?
Architecture: (1) API Layer — FastAPI behind ALB, auto-scale ECS tasks, (2) Query Processing — async request handling, query expansion with LLM, (3) Retrieval — Pinecone with multiple index replicas, connection pool, (4) Cache Layer — Redis for semantic caching (embed query, find nearest cached query within cosine sim 0.95), (5) LLM Layer — multiple OpenAI API keys with round-robin + fallback to Azure OpenAI, (6) Monitoring — request tracing, latency p99, cost per query. At 10k QPM, caching becomes critical — aim for 60%+ cache hit rate.
Design a real-time ML feature pipeline for an AI recommendation system.
Components: (1) Data Ingestion — Kafka streams for user events, (2) Stream Processing — Flink/Spark Streaming for real-time feature computation, (3) Feature Store — Feast with online store (Redis for <5ms reads) + offline store (S3/BigQuery for training), (4) Model Serving — TorchServe/Triton with A/B testing support, (5) Monitoring — Evidently for data drift, Prometheus for latency. Key challenge: keeping online and offline features consistent. Use same feature computation logic for both.
50+ questions locked
Unlock the full System Design pack
Detailed answers, real company context, and practice mode — all in one course.
Ready to nail your System Design interview?
10-question AI readiness check → personalised study plan.
Take Free Assessment →