Hire a forward deployed engineer or outsource? A guide for growing companies

You have identified use cases for AI agents and you need someone to get them into production. The ideal profile has a name: forward deployed engineer. The catch: it is rare, in heavy demand from large vendors and AI companies, and hard to assess for a business without a technical team. This guide helps you choose between hiring, a freelancer or outsourcing to a team that works in a forward deployed way.

The profile you are looking for

An FDE combines skills that rarely come together (see the full definition):

• Real developer depth: production code, APIs, databases, deployment.
• Hands-on command of language models, RAG, agents and their evaluation.
• The ability to understand your business and talk with non-technical teams.
• Autonomy to move without a complete spec, and a focus on outcomes.

When hiring in-house makes sense

• AI is central to your strategy, with a multi-year roadmap.
• You have several use cases to deploy and maintain continuously.
• You already have a technical team able to manage and assess this profile.
• Confidentiality requirements mean the expertise must stay in-house.

The hidden costs of hiring

• Time to hire: months for a rare profile, while projects wait.
• Risk of a bad hire: without a technical lead, it is hard to tell a real FDE from someone who has only followed tutorials.
• Isolation: a lone FDE has nobody to review their code or cover their holidays.
• Retention: AI profiles are heavily headhunted, and a departure takes system knowledge with it.
• Tooling: hosting, licences, evaluation and monitoring tools on top of salary.

How to interview an FDE candidate

1. A real case study: give them one of your processes and ask how they would turn it into an agent, with what data, what risks and what metrics.
2. A code review of something they shipped to production, not a prototype.
3. The evaluation question: how would they know the agent is right? An answer with no test set is a red flag.
4. A stakeholder exercise: explain an AI limitation to a sales or finance lead.
5. Security: how would they handle access rights and personal data?

The freelance option

An independent FDE can start fast and costs less on a short project. The limits are well known: variable availability, no review or cover, knowledge that leaves at the end of the engagement. It is a good fit for a prototype or a short-term boost to an existing team, less so for a critical agent that must be maintained.

The forward deployed team option

An external team working in a forward deployed way brings the same field commitment, with several advantages for a growing company:

• Fast start, with no recruitment.
• Multiple skills: development, AI, integration, security, interface design.
• Continuity: code review, cover during absences, documentation.
• Project-based cost, then a monthly care plan once the agent is live.
• Knowledge transfer to your teams, so you stay in control of your tools.

The condition: the team must commit to production and adoption, not just a prototype. Our comparison of FDE vs solutions engineer vs consultant helps you ask the right questions.

The decision grid

• A first use case to validate: an external forward deployed team.
• A short-term boost for an existing tech team: a freelancer.
• Several critical agents and a long roadmap: hire in-house, possibly with an external team to get started.
• An agency reselling AI to its clients: a white-label partner.

What we offer

Our AI agents service works as a forward deployed team for growing companies: we embed with your people, build and ship in your environment, then run ongoing care or hand maintenance over to your team. We work in English and French across time zones from Europe to the US East Coast. Let's talk about your first use case.