What exactly is a forward deployed engineer?
A forward deployed engineer is a software or AI engineer who works embedded inside a client's organisation rather than building from the outside. They own the full implementation cycle — from scoping and architecture to deployment and iteration — and are directly accountable for outcomes, not just deliverables.
How is this different from AI staff augmentation?
AI staff augmentation typically adds multiple specialists to your team across different roles (ML engineers, data scientists, MLOps). A forward deployed engineer is a single senior operator with broad ownership — closer to having a founding engineer embedded in your team than a contractor filling a gap. They own the problem, not just the task.
How quickly can an FDE start?
For most engagements, we can match and onboard a forward deployed engineer within 2–4 weeks. We shortlist candidates against your tech stack, domain, and timeline requirements before any introductions — so time spent in the process is minimal.
Does the FDE come with a tech lead or support team?
Yes. Every Netguru FDE is backed by our internal engineering community — architecture review, code standards, and escalation paths are built in. For larger engagements, we can also pair the FDE with supporting specialists (data engineers, MLOps, QA) as the scope evolves.
What engagement models do you offer?
We offer full-time embedding (standard), part-time advisory (2–3 days per week), and project-based engagements with a defined scope and timeline. We'll recommend the right model after an initial scoping call — most clients start full-time and adjust as the AI product matures.
How much does a forward deployed engineer cost?
Netguru FDE engagements are structured on a Time and Materials basis — you pay for actual engineering hours rather than a fixed project estimate. Most full-time FDE engagements start at a monthly retainer; part-time advisory and project-based scopes are also available. We'll share transparent rate information on an initial scoping call once we understand your stack and timeline.





