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Prep plan
Updated weekly · Last refresh Aug 30

Capgemini AI Engineer Interview Questions

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

24questions
~4htotal time
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1
CodingStart here. 5 questions · ~44 min
2
NLP3 questions · ~27 min
Fine-Tuning vs Prompt EngineeringHard

Compare when to fine-tune a language model versus use prompt engineering, with practical trade-offs in quality, cost, and maintenance.

Language ModelsTrade-offsUser NeedsCapgemini
Choosing Domain EmbeddingsMedium

Tests your ability to choose and justify embedding models for domain-specific retrieval quality.

model selectionCapgemini
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3
System Design4 questions · ~36 min
Design an LLM Serving PlatformHard

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

Cold StartFeature StoreModel ServingCapgemini
Design Multi-Agent Customer ServiceMedium

Assesses your system design approach for multi-agent architectures in customer-facing workflows.

multi-agent systemsCapgemini
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4
Generative AI & LLMs4 questions · ~36 min
Vector vs Keyword Retrieval Trade-offsMedium

Evaluates your understanding of retrieval methods and when to use each in production systems.

Vector SearchCapgemini
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5
Behavioral & Leadership4 questions · ~36 min
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6
More topics4 questions · ~36 min
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-tuningCapgemini
Evaluate LLMs in ProductionMedium

Assesses how you measure and validate LLM performance with real-world constraints and metrics.

performance metricsLLM EvaluationproductionCapgemini
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The finish line: interview-readyComplete all 24 questions to finish this plan.