What is a forward deployed engineer, and when do you need one?
aiWize team 5 min read
A forward deployed engineer (FDE) is an engineer who works inside your team rather than at a distance. FDEs set up your AI stack, build AI agents and automate processes alongside your people, in your systems. You need them when you're ready to build working AI, not just plan it.
What does a forward deployed engineer do?
The name comes from software companies that sent engineers to work on site with customers, close to the real problem. The idea now fits AI well. The gap between a promising demo and working software is often wide.
For a buyer, the point is simple. An FDE joins your team and builds with you, inside your systems. Typical work includes:
- Setting up your AI stack. That is the models, data connections and security your AI tools run on.
- Building AI agents for specific workflows. An AI agent is software that uses a large language model to finish a task, not just answer a question.
- Connecting AI to the systems you already use, such as email, a CRM or a shared drive.
- Adding checks, approvals and logs, so people stay in charge.
- Training your team and handing over, so you can run it yourselves.
How is an FDE different from a consultant or an agency?
All of them can help. The difference is where the work happens and what you are left with at the end.
| Question | Typical consultant or agency | Forward deployed engineers |
|---|---|---|
| Where do they work? | Mostly at a distance, with set check-ins | Inside your team and your systems |
| What do they deliver? | A plan, or software built elsewhere | Working AI in your own systems |
| How do they learn your work? | Through workshops and documents | By working next to the people who do it |
| What are you left with? | A report or a handover pack | Working tools, plus a team trained to run them |
Each model has its place. A strategy question may only need advice. A build in your own systems benefits from engineers who sit with your team.
When do you need forward deployed engineers?
Embedded AI engineers make sense once you know what you want to build. You have found a process that AI can take over, and the business case is clear. Now you need it working in your own systems.
They also help when your systems are complex. Real data is messy. Access rules are strict. Older software does not always connect easily. Engineers who sit with your team work through these problems faster. They can ask the right person straight away.
And they suit companies that want to learn as they build. Your people work next to the engineers, so the skills stay with you after the engagement ends.
When don't you need one?
FDEs are not the first step for everyone. If you're still choosing tools or training people, start there. An embedded team is hard to justify before you know which processes matter.
You may also not need one if a ready-made tool does the job. Sometimes buying is faster and cheaper than building. A good adviser will tell you so. For ideas on where AI agents fit, see AI agents at work.
What should you look for in forward deployed engineering services?
If you decide to bring in FDEs, a few questions help you compare providers.
- Do they work inside your systems, or build elsewhere and hand over?
- Are they vendor-neutral, or tied to one model or platform?
- How do they keep people in charge, with approvals and logs?
- How do they train your team and hand over?
- Do they help with governance, or only the build?
Ask about models too. Some builds run on paid AI tools. Others run on open models you host yourself. Our guide to open models versus paid AI tools explains the trade-offs.
How does an embedded engagement run?
Engagements differ, but most follow a similar shape. Ours runs in a simple order.
- Scope: a free call, then a short discovery with your team.
- Build: our engineers ship agents in your systems, working alongside your people.
- Hand over: we train your people, set up governance and stay on hand.
How aiWize helps.
An embedded engineering team is one of our two ways to work with aiWize. Our forward deployed engineers set up your AI stack and build AI agents for your workflows. They automate processes end to end, then train your team to run them.
We're vendor-neutral, so we choose models and tools that fit your needs. If you're not ready to build yet, we also offer consulting and training. To talk about your first build, talk to an engineer.
Common questions.
What does a forward deployed engineer do day to day?
An FDE spends most of their time inside your team. A typical day might include meeting the people who do the work and mapping a process. It might also mean connecting AI to your systems, testing an agent and showing the team how it works. The aim is working software, not slides.
Is a forward deployed engineer the same as a consultant?
Not quite. A consultant often advises and recommends. A forward deployed engineer builds. FDEs work inside your team and systems, turn a plan into working software and train your people to run it. Some providers, including aiWize, offer both advice and embedded engineers, so you can start with either.
Do we need our own engineers to work with FDEs?
It helps, but it isn't essential. FDEs work best with someone on your side who knows the process and someone who can grant system access. If you have an IT or data team, they learn alongside the FDEs and take over at handover. If not, we train the people who will run it.