CGI GenAI Engineer Interview Questions
The questions to prepare for a CGI GenAI Engineer interview. Questions from real interview reports rank first. Updated daily.
Compare production LLM deployment architectures and explain trade-offs across latency, cost, quality, reliability, and operations.
CGIDesign a low latency RAG system over millions of documents, with scalable retrieval, ranking, generation, and production monitoring.
CGITalk through a real generative AI project, focusing on architecture, evaluation, hallucination risk, and how you handled safety issues in practice.
CGIDiscuss the main ethical risks in deploying generative AI, including hallucination, misuse, privacy, and governance.
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Explain how random forests work, why they reduce variance, and when they are a good choice.
CGIApproach for continuously monitoring a deployed model and keeping performance stable as data changes.
CGITests practical coding skills for data cleaning and handling missing data correctly.
CGITests your ability to design production-ready ML pipelines across data, training, and deployment.
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