Target AI Engineer Interview Questions

Design a grounded customer support RAG pipeline covering retrieval, prompts, generation, evaluation, latency, cost, and safety.

Vector SearchHallucinationPrompt EngineeringTarget

Design a practical document chunking and indexing pipeline for accurate, efficient vector search.

Vector SearchLanguage Modelssearch relevanceTarget

Design a practical framework for comparing LLM quality, reliability, latency, cost, and safety in production.

performance evaluationevaluation metricsMetricsTarget

Compute cosine similarity for equal-length high-dimensional vectors using dot products and Euclidean norms.

function implementationArraysArray ManipulationTarget

Design a low-latency, high-concurrency LLM serving layer with effective prompt, response, and KV-cache strategies.

high-frequency requestsinference latencyml inferenceTarget

Approach for detecting, interpreting, and responding to model drift in a production AI system.

CalibrationAUC-ROCThreshold TuningTarget