Design Human-In-The-Loop And Permission Controls For RAG
Company: Wayfair
Role: Software Engineer
Category: Machine Learning
Difficulty: medium
Interview Round: HR Screen
Answer technical questions for an AI platform role: how would you design human-in-the-loop review for a RAG system, and how would you ensure users can only see content they are authorized to access?
```hint Hint 1
Start by naming the core entities, constraints, and success criteria.
```
```hint Hint 2
Make the trade-offs explicit before going deep on implementation details.
```
### Constraints & Assumptions
- The system uses retrieval-augmented generation over permissioned documents.
- Human review may be used for feedback, quality control, or approvals.
- Access control must apply to both retrieved context and generated answers.
- The answer should be practical for an enterprise platform.
### Clarifying Questions to Ask
- Who are the reviewers and what authority do they have?
- Is human review required before every answer or only sampled?
- What permission model exists for source documents?
- Can generated answers contain snippets from restricted documents?
- What audit requirements apply?
### What a Strong Answer Covers
```premium-lock What a Strong Answer Covers
```
### Follow-up Questions
- How would you prevent permission leakage through cached retrieval results?
- How would you sample answers for review?
- What would you log for audits?
- How would reviewer feedback improve retrieval or generation?
Overview: Review RAG platform design questions about human-in-the-loop review and permission-aware retrieval. The prompt focuses on reviewer workflows, access-control filters, permission-safe caching, grounded answers, audit logs, and quality metrics.