Top 49
Prep plan
Updated weekly · Last refresh Oct 17

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 daily.

49questions
~7htotal time
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1
Machine LearningStart here. 8 questions · ~64 min
Fine-Tuning vs RAG vs PromptingMedium

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

Optum
Fine-Tuning vs Prompted APIsMedium

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

Trade-offsPrompt Engineeringmodel fine-tuningOptum
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2
System Design20 questions · ~160 min
Design Agent Workflow Memory ManagementMedium

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

agent workflowsmemory managementstate managementOptum
Design an LLM Serving PlatformHard

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

Cold StartFeature StoreModel ServingOptum
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3
Pipelines5 questions · ~40 min
CI/CD Pipeline for AI ModelsMedium

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

InfrastructureToolsQualityOptum
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4
Generative AI & LLMs4 questions · ~32 min
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-TuningOptum
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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5
Behavioral & Leadership11 questions · ~88 min
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6
More topics1 question · ~8 min
Evaluate Agents Beyond AccuracyMedium

Evaluates your ability to define meaningful metrics and tests for agent quality and reliability.

performance evaluationMetricsAccuracyOptum
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