Should we hire an AI engineer or work with an agency?
Hire in-house when AI work will be continuous and you already have someone senior to guide the hire. Use an agency when the work is a defined project, when speed matters, or when a first AI hire would have no one to learn from — a lone junior AI engineer with no mentor is the most common way these programmes stall.
| In-house hire | Agency | |
|---|---|---|
| Time to first output | 3–6 months, hiring included | 1–4 weeks |
| Cost shape | Fixed salary, indefinite | Scoped to the project |
| Breadth of skill | One person's depth | A team across ML, data, and infrastructure |
| Risk if it doesn't work | A difficult and slow correction | The engagement ends |
| Long-term ownership | Built in from day one | Needs an explicit handover plan |
Choose in-house hire when
- AI work will be continuous for years, not a project with an end date.
- You have a senior engineer or CTO who can evaluate candidates and mentor the hire.
- The domain takes months to learn and the knowledge is worth holding internally.
- You can wait a quarter or two for the first working system.
Choose agency when
- The work is a defined project with a clear finish line.
- You need something in production this quarter.
- Nobody on staff has shipped a model to production, so a first hire would have no one to learn from.
- The project needs several specialisms at once — ML, data engineering, infrastructure — which is more than one hire provides.
The comparison is usually framed as a cost question — an agency month against a monthly salary — and that framing hides the risk that actually matters.
A first AI hire into an organisation with no existing AI expertise is a difficult position to fill and a difficult one to occupy. The candidate has no one to review their work, no established practice to inherit, and every architectural decision lands on them alone. Strong engineers frequently decline that role, and the ones who accept it often leave, taking the only institutional knowledge with them.
That is the case for starting with a partner even when you intend to build a team: the first system gets built and running, it establishes the patterns and the evaluation practice, and your eventual hire inherits something working rather than a blank page. Hiring into a functioning system is a materially easier sell than hiring into an empty one.
The failure mode on the agency side is real too, and it is worth being direct about: an engagement that ends with code your team cannot operate has moved the problem rather than solved it. Guard against it in the contract — code in repositories under your organisation, documentation written for your engineers, and a handover that is a scheduled phase rather than a final email.
Got an idea? Let's make it real.
Tell us about your problem. We'll come back within one business day with a take, a rough plan, and a call invite.