How to Hire Your First AI Engineer

What the role actually involves, what to test for, and the mistakes that lead to an expensive mis-hire.

Every company now wants an AI engineer. Few can describe what the person will do on a Tuesday afternoon. That gap is where most first AI hires go wrong: the job description asks for a researcher, the work needs a builder, and six months later everyone is disappointed.

Decide what you are actually hiring for

There are at least three different jobs hiding under the title. A machine learning engineer trains and deploys models on your data. A generative AI engineer builds products on top of large language models: retrieval, agents, prompts, evaluation. An AI platform engineer makes the data and infrastructure ready for both. For most companies making a first hire, the second profile is the right one, and it looks more like a strong software engineer than a scientist.

Look for engineering habits, not paper

Certifications and courses are easy to collect. What matters is whether the person has shipped something that other people used. Ask them to walk through one project end to end: where the data came from, how they measured whether it worked, what broke in production, and what they would do differently. Vague answers about "fine-tuning" with no numbers are a warning sign.

Test with a small, real task

A two-hour take-home that mirrors your actual problem tells you more than any interview. Give them a messy sample of your documents or data and ask for a working notebook plus a short note on limitations. You are looking for clean code, honest evaluation and clear communication, not a perfect result.

Check they can say no

The best AI engineers spend a lot of time explaining why something should not be built with AI, or not yet. In the interview, describe a use case that is a poor fit and see whether they push back.

Set them up to succeed

One engineer cannot fix your data platform, build the product and educate the company at the same time. Before they start, make sure the data they need is accessible, a business owner is assigned to the first use case, and success is defined in numbers. If you cannot do that yet, a short readiness assessment before hiring will save you a salary.

If you cannot find one

Senior AI engineers are scarce and expensive. A screened contract engineer, or a small outsourced team to deliver the first use case while you hire, is often the faster route. MSRK Tech does both, and we are happy to tell you which fits.