Optum Agentic AI Engineer Interview Questions

The questions to prepare for a Optum Agentic AI Engineer interview. Questions from real interview reports rank first. Updated weekly.

12questions

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Behavioral & LeadershipStart here. 5 questions · ~40 min

Explaining Technical Trade-offs ClearlyMedium

Tests whether you can translate complex engineering trade-offs into clear business decisions for non-technical stakeholders.

technical communicationTrade-offsStakeholder Management

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More topics7 questions · ~56 min

Compare when to fine-tune a foundation model versus relying on prompt engineering with a managed API.

Design state and memory management for long running agentic workflows with retrieval, persistence, serving, and failure handling.

Approach LLM Fine-Tuning for TasksMedium

Explain a practical approach to fine-tuning an LLM for a specific task, including data, evaluation, and hallucination risks.

Prompt EngineeringLLM EvaluationFine-Tuning

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CI/CD Pipeline for AI ModelsMedium

Design a CI/CD pipeline for AI model deployment with automation, orchestration, infrastructure, and quality gates.

InfrastructureToolsQuality

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Fine-Tuning vs RAG vs PromptingMedium

Choose between prompting, RAG, and fine-tuning based on task stability, knowledge freshness, and evaluation results.

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Design an LLM Serving PlatformHard

Design an LLM serving system that balances latency, cost, scalability, and safety for production traffic.

Cold StartFeature StoreModel Serving

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Fix Hallucinations in RAG AnswersEasy

Reduce hallucinations in a RAG system even when retrieval is already correct, using grounding, verification, and evaluation.

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