Top Azure AI Advanced Interview Questions (2026) with clear, practical answers — curated for 2026 interviews. Pair these with a deployed project from our AI, GenAI & Agentic AI training.
What is Azure OpenAI Service and how does it differ from OpenAI?
Managed access to OpenAI models (GPT, embeddings) inside Azure with enterprise networking, RBAC, private endpoints, content filtering and regional data handling — the enterprise-governed way to use these models.
How do you build enterprise RAG on Azure?
Ingest + chunk documents, embed them, index in Azure AI Search (vector + hybrid/semantic), retrieve at query time, and generate with Azure OpenAI — with access control trimming so users only see permitted data.
What is Azure AI Search’s role in RAG?
It is the retrieval layer — vector, keyword and hybrid search with semantic re-ranking and security filters. Retrieval quality usually matters more than the model for answer accuracy.
What are PTUs?
Provisioned Throughput Units — reserved capacity for predictable latency/throughput on Azure OpenAI, vs. pay-as-you-go token billing. Used for production workloads with SLAs.
How do you handle responsible AI / safety on Azure?
Azure AI Content Safety (harm filtering), prompt-injection mitigations, groundedness checks, and the Responsible AI tooling for evaluation, red-teaming and monitoring.
What is Prompt Flow?
An Azure AI Studio tool to author, test, evaluate and deploy LLM pipelines (prompts + tools + Python) with built-in evaluation and versioning.
How do you evaluate and monitor an Azure AI app?
Offline eval sets (groundedness, relevance, fluency), online monitoring of latency/cost/quality, and regression tests on prompts — surfaced in Azure AI Studio / Application Insights.
How do you secure an Azure OpenAI deployment?
Private endpoints + VNet, managed identity + RBAC (no keys in code), content filtering, logging, and data-zone/region controls for compliance.