The Latent Memory Paradox

Senior AI Engineer interview at OpenAI, and the interviewer asks:

“You spent months fine-tuning our enterprise LLM to explicitly mask PII and withhold sensitive financial data. Your validation safety metrics are flawless. Why is your production model still fundamentally vulnerable to leaking that exact information to a malicious user?”

Don’t say: “It’s an edge-case distribution issue. We need to expand the fine-tuning dataset with more adversarial examples, increase the safety penalty in the loss function, and run another RLHF pass to cover the long tail of prompts.”