Forward deployed engineers (FDE)
Senior engineers embedded inside your team, working in your codebase and your standups, accountability of an employee, flexibility of a partner.
Discuss an embedded engineering needWhat is a forward deployed engineer (FDE)?
AI forward deployed engineers
An AI forward deployed engineer is the same embedded model, specialized for AI work: an engineer who joins your team to ship LLM features, agents, or AI-native product changes inside your existing codebase, not as a separate research project. AI FDEs carry the same accountability as any Codiot FDE, with the added judgment to know when an AI approach is the right tool and when it isn't.
FDE vs consultant vs contractor.
| Forward-deployed engineer | Consultant | Contractor | |
|---|---|---|---|
| Primary goal | Make the software work for a specific user or account | Advise and recommend | Deliver assigned tasks |
| Writes production code | Yes, in your systems | Rarely | Yes, to spec |
| Works | Embedded with the customer or team | In workshops and reviews | From a remote task queue |
| Feedback to product | Continuous, from the field | Occasional | Little |
| Best when | Adoption keeps stalling after the sale | You need direction | You need extra hands |
What we build.
Embedded in your workflow
Your Slack, your sprint planning, your codebase, not a separate team working from a different backlog.
Senior-only placement
FDEs are engineers with years of production experience, not junior staff learning on your dime.
Flexible engagement length
From a single quarter to an open-ended placement, scaling up or down with your roadmap.
AI forward deployed engineers
FDEs who specialize in shipping AI features and agents inside existing products, not building AI in isolation.
Direct hand-off option
If you later want to hire the engineer directly, that path is built into the engagement, not blocked by it.
How it works with Codiot.
Match the profile
We place an engineer whose stack and domain experience actually fits what your team is building.
Embed in week one
Access, onboarding, and a seat in your existing rituals from day one, not a slow ramp-up.
Review and adjust
Regular check-ins on fit and output, with the option to swap or scale the engagement as needs change.
Stack we use, and why teams choose us.
- ·Senior engineers only, no hand-offs to juniors mid-project
- ·Overlap hours with US/EU time zones
- ·Weekly demos and a single point of contact
- ·Code you own, documented and tested
When it fits, and when it doesn't.
Signs you need this
- ·A capable product still is not landing inside a specific customer or team.
- ·You need engineers embedded with users, not at arm's length.
- ·Deployment, integration, and adoption keep stalling after the sale.
- ·Complex, high-touch accounts need engineering attention in context.
What's included
- ·Engineers embedded with your customer or team to make software work in the real world.
- ·Integration, customization, and adoption support in context.
- ·A feedback loop from the field back into the product.
- ·Hands-on delivery, not just advisory.
What's not
- ·Ongoing staff augmentation with no product-adoption goal.
- ·Replacing your product or sales team.
- ·Open-ended presence beyond the outcome that was scoped.
When this isn't the right fit
- ·Your product self-serves and adoption needs no embedded engineering.
- ·The work is generic development better handled by a standing team.
- ·There is no specific deployment or account for the engineer to own.
Common questions, answered plainly.
What is a forward deployed engineer?
What is an AI FDE?
How is this different from an extended product team?
How much does an FDE cost?
How fast can an FDE start?
Explore related work.
Let's talk about a forward deployed engineer (FDE).
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