Brillio AI Engineer Interview Questions

Design an LLM serving architecture that manages long generation latency, GPU efficiency, reliability, and model quality.

gpu hardwareinference latencyModel ServingBrillio

Design reliable communication, shared state, safety controls, and evaluation for a multi-agent financial analysis system.

Hallucinationmulti-agent systemstool useBrillio

Design layered defenses, evaluations, and operational controls for prompt injection in a public-facing LLM application.

llm deploymentPrompt InjectionSecurityBrillio

Choose between fine-tuning and RAG for Anduril domain knowledge while balancing freshness, cost, latency, hallucination, and security.

RAGmodel fine-tuningmodel comparisonBrillio

Design and fine-tune an embedding model by matching objectives, data, architecture, retrieval metrics, and deployment constraints.

model selectionMachine LearningWord EmbeddingsBrillio

Select and justify the evaluation metrics needed to move an LLM from prototype testing to reliable production monitoring.

evaluation metricsMetricsModel MetricsBrillio