Skip to content

LLMOps & Production AI interview questions

Observability, prompt tracing, cost management, drift detection, CI/CD pipelines for prompts & evals, and production telemetry.

What to study

  • Distributed tracing for multi-step agent and RAG pipelines.
  • Cost budgeting, rate limiting, and fallback LLM routing.
  • Monitoring model drift, data distribution shift, and latency SLAs.

Questions and answers

  1. How do you implement distributed tracing for multi-step LLM pipelines?

    Intermediate · 2 min read

  2. What is LLMOps and how does it differ from traditional MLOps?

    Beginner · 2 min read

  3. How do you monitor LLM token usage, latency, and costs in production?

    Beginner · 2 min read

  4. How do you implement fallback routing and rate limiting for LLM APIs?

    Intermediate · 2 min read

  5. How do you detect and mitigate data and concept drift in production LLMs?

    Advanced · 2 min read

  6. What is prompt versioning and why is it essential?

    Beginner · 2 min read

  7. What is an OpenTelemetry span in LLM tracing?

    Beginner · 2 min read

  8. How do you budget and cap monthly LLM API costs?

    Beginner · 2 min read

  9. How do you build a canary deployment pipeline for prompt updates?

    Intermediate · 2 min read

  10. How do you architect real-time anomaly detection for rogue agent spends?

    Advanced · 2 min read

  11. What is structured logging for LLM prompts, completions, and token metrics?

    Beginner · 2 min read

  12. What is cost attribution modeling per user, team, and organization in LLM applications?

    Beginner · 2 min read

  13. What is SLA/SLO monitoring for Time-to-First-Token (TTFT) and throughput (Tokens/sec)?

    Beginner · 2 min read

  14. What is semantic versioning for prompts and model configurations in production deployments?

    Beginner · 2 min read

  15. What is fallback configuration when primary LLM providers return 5xx errors?

    Beginner · 2 min read

  16. How do you set up automated prompt regression pipelines in GitHub Actions CI/CD?

    Intermediate · 2 min read

  17. How to detect semantic drift in user queries using embedding clustering over time?

    Intermediate · 2 min read

  18. How to build a continuous evaluation pipeline sampling production traces for human review?

    Intermediate · 2 min read

  19. How to design an enterprise-grade LLM Gateway with dynamic fallback, tenant rate limiting, and cost allocation?

    Advanced · 2 min read

  20. How to handle confidential enterprise telemetry and PII sanitization in compliance-heavy industries?

    Advanced · 2 min read

Study LLMOps & Production AI with progress tracking