AI Engineer Recruiting in LatAm

AI Engineering Recruiting
Wizhire recruits Senior, Staff, and Principal AI Engineers from Latin America. AI Engineering is the application layer: LLM integration, RAG architectures, agent frameworks, evaluation pipelines, and the orchestration that connects AI capabilities to production products. The core artifact is a shipped AI-powered application, not a trained model.

The Signal Wizhire Screens For in AI Engineering
The most common uninformative signal in AI engineering interviews: "I built a chatbot." Everyone has built a chatbot. The signal is what comes after:
How did they evaluate quality? What was the failure rate? How did they handle hallucination? What was their retrieval strategy and why? How did they handle prompt injection? What happened when users tried to break it?
Evaluation separates levels more cleanly than any other skill in AI engineering. An IC2 doesn't evaluate. An IC3 evaluates manually. An IC4 designs evaluation frameworks for their features. An IC5 designs evaluation infrastructure for the org.

How Wizhire Evaluates AI Engineers
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AI Implementation: problem decomposition for AI vs. deterministic code, prompt engineering systematically (not trial-and-error), RAG implementation with quality measurement, agent design with appropriate control
AI System Design: retrieval architecture design, orchestration and prompt architecture, safety and guardrails architecture, evaluation architecture, cost and latency optimization from the start
Production Awareness: prototype-to-production gap is the defining challenge. Has the candidate shipped AI to real users at scale — handled production latency, cost management, safety incidents, quality degradation under real traffic?
Foundation Model Landscape: can select an appropriate model for a task with trade-off analysis, not "we use GPT-4 for everything"