Most teams that want to hire AI developers have already tried something. A freelancer built a demo that never reached users. An agency delivered a project, then left nobody who understood it. A senior hire took four months to find. None of these is a bad route. Each fits a different kind of work, and most of the pain comes from picking the wrong one.
This guide covers the four common ways to hire AI developers, what each is good at, where each goes wrong, and how to choose.
First, be clear about the work
Before you compare options, write down three things.
- What has to ship. "An AI assistant" isn't a scope. "Answers from our help centre, with a citation on every answer, live for paying customers" is.
- How long it lasts. A fixed piece of work with an end date is a project. A product that keeps changing needs someone who stays.
- Who owns it afterwards. If nobody on your team can maintain the result, whoever builds it has to leave the code, the tests and the decisions written down.
Most AI work is the second kind. Models change, prompts drift, users find edge cases, and evals need updating. That's why the choice of who you hire matters more than for a one-off website.
Option 1: a freelance AI developer
Good for: a contained task with a clear finish line, such as a prototype, an integration or a proof of concept you plan to throw away.
Watch out for:
- Availability. A good freelancer is usually on several projects at once.
- Continuity. When the contract ends, the knowledge leaves with them.
- Vetting falls on you. A portfolio of demos looks the same as a portfolio of shipped products.
Ask: "Show me something you built that real users still use, and tell me what broke after launch."
Option 2: an agency, on a fixed scope
Good for: a defined project where you want one party responsible for delivery, and you don't plan to change much afterwards.
Watch out for:
- Fixed scope fights change. AI features almost always change once real users touch them.
- Handover. Ask early who will maintain it, and what documentation you get.
- Who actually does the work. The senior people in the sales call aren't always the people writing the code.
Ask: "Who writes the code, and can I talk to them before we sign?"
Option 3: hire in-house
Good for: AI that is central to your product for years, when you can afford the time to hire and the salary to keep someone.
Watch out for:
- Time. Senior AI engineers are slow to find, and a long search delays the work.
- Risk. A wrong senior hire is expensive to reverse.
- Isolation. One AI engineer on a team with no one to review their work often slows down.
Ask yourself: "Do we have the work, and the people to review it, for a full-time hire this year?"
Option 4: an embedded AI-native engineer
This is the model Wanile works in, so read this section with that in mind.
An embedded engineer works inside your team. They're in your repo, your standups and your tools, on your priorities, with no separate project plan. They stay as long as the work needs them, month to month.
Good for: product work that keeps changing, where you want senior hands quickly without a long hiring process, and where your own team stays in charge.
Watch out for:
- You still need to lead. An embedded engineer works best with a clear owner on your side who sets priorities and reviews work.
- Fit matters more than a CV. Ask for a trial on real work before committing.
Ask: "Can I meet the actual engineer, and can they start on a real task before I commit?"
What "AI-native" adds
Whichever route you choose, look for developers who are AI-native in two senses.
- They build with coding agents, and review everything. Agents write the routine code, tests and first drafts. The engineer keeps the judgement and reads every line before anyone else sees it.
- They build AI into products that hold up. An eval set before any tuning, citations users can check, an approval step before anything irreversible, and personal data kept out of prompts.
An AI developer who has only one of these is half the hire. Our guide to hiring an AI-native engineer has the interview questions and a day-by-day plan for a 7-day trial.
A quick way to choose
- A throwaway prototype in two weeks: a freelancer.
- A defined project that won't change much: an agency on a fixed scope.
- AI at the centre of your company for years, and time to hire: in-house.
- Product work that keeps changing, and you need someone senior now: an embedded AI-native engineer.
Teams often combine them: an embedded engineer ships the first version while you hire in-house, then hands over properly.
How to hire AI developers through Wanile
You meet the engineers before anything starts, and the first 7 days are a free trial on a real task from your backlog, against success criteria agreed on day one. Code and IP are yours from the first commit. If it works, you keep the engineer month to month.
The engineers are on their profiles, the process is on How we work, and what AI-native means in practice is on hire AI-native engineers.