Design a natural-language AEP Q&A assistant
Company: Adobe
Role: Machine Learning Engineer
Category: ML System Design
Difficulty: hard
Interview Round: Onsite
Design a natural-language assistant for Adobe Experience Platform (AEP) to help marketers:
(
1) answer questions about any product functionality strictly using public-facing AEP documentation;
(
2) answer questions about the customer’s own data stored in AEP (e.g., “How many datasets do I have?”, “What are the top 5 biggest audiences by population?”) via secure summarization. Specify the end-to-end architecture (document ingestion, indexing, retrieval, grounding/orchestration, LLM selection, prompt design), authorization and data-access controls for tenant-scoped data, guardrails for scope-limited Q&A with a default refusal message for out-of-domain queries, latency/SLA targets, privacy/PII handling and auditability, evaluation/monitoring strategy, and how the system handles example questions like authentication steps and creating rule-based audiences. Provide proposed APIs, schemas, and a deployment plan.
Quick Answer: This interview question evaluates ML product requirements, data/labeling, modeling, serving architecture, evaluation, monitoring, and trade-offs in a realistic interview setting. A strong answer for Design a natural-language AEP Q&A assistant states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.