How to Hire Your First AI Engineer: Red Flags to Watch For

The Talent Market Is a Minefield

Salaries for AI engineers are insane. You cannot afford a mis-hire. Everyone adds "AI Expert" to their LinkedIn today. Here is how to test if they actually know the math and the stack.

The Three Tests

1. Ask about evaluation. If they do not know how to test if the model is working, they are amateurs. Any real AI engineer can explain precision, recall, and how they measure output quality in production.
2. Ask about costs. If they do not mention token usage, latency, or cost optimization, run. Production AI is fundamentally a cost management problem. Models are expensive. Engineers who ignore this will burn your budget.
3. Test for RAG. Ask them how they handle context limits. If they cannot explain chunking strategies, embedding models, and retrieval evaluation, they have only used ChatGPT's web interface.

Bonus Red Flags

• They talk about "training models" when you need API integration
• They cannot explain the difference between fine-tuning and few-shot prompting
• They have never deployed an AI system to production
• They confuse "prompt engineering" with "AI engineering"
• Their portfolio is only Jupyter notebooks, not production applications

The Alternative

Or, don't hire full-time. Use a fractional team for the cost of one junior engineer. You get senior expertise across the full stack without the risk of a bad hire.

At CTO Copilot, our team has shipped AI systems in production across fintech, healthcare, e-commerce, and operations. We can move faster than a new hire who needs three months to ramp up.