To hire a forward deployed engineer, look for three things in one person: production engineering, ease working face to face with the people who run the process, and enough domain sense to spot the exceptions. Hire in-house when you have a steady pipeline of AI work and someone to lead it. Bring one in as a service for the first workflow.
#Key takeaways
- A forward deployed engineer combines production engineering, client-facing work and domain judgement, which makes the role hard to fill.
- Demand for the title has grown fast, so a mid-sized operations company competes with software firms for the same people.
- The best interview signal is a system the candidate put into production and what broke after go-live, not a demo.
- Hire in-house for a steady pipeline of AI work with a technical leader to manage it; bring one in when you need the first workflow running.
- The first assignment should be one workflow with a named owner, a baseline and a written handover, not a platform.
#What does a forward deployed engineer actually need to be good at?
The role is three jobs in one. The engineer writes and ships production code into your systems: the ERP, the CRM, the ticket queue, the shared drive. They sit with the people who run the process and get the real version out of them. And they know the domain well enough to ask why an invoice is on hold before anyone explains.
- engineering: integrations, evaluation of AI output, logging and rollback.
- client-facing work: running a workshop, saying no to a department head, writing a spec a manager can sign.
- domain judgement: knowing which exceptions matter and which can wait.
The canonical definition, and how the role compares with a consultant, an in-house engineer and staff augmentation, is on what is a forward deployed engineer. This post covers hiring one.
#Why is a forward deployed engineer so hard to hire?
Partly demand. Job postings for the role on Indeed rose from 643 in april 2025 to 5,330 in april 2026, according to newsbytes, citing indeed data, 2026.
Partly the mix. Strong engineers who enjoy sitting with an accounts payable team are rare. A CV full of model work says little about whether the person can get a workflow past a sceptical operations manager and into daily use.
#What should you look for in the interview?
- Ask for a system they put into production, who used it, and what broke after go-live.
- Hand them a messy real example, such as a vendor statement to reconcile against an SAP or Odoo export in Excel, and ask how they would map the workflow before building.
- Give them an Arabic or mixed-language document from your own work and ask how they would test the output.
- Ask to see a runbook or handover note they wrote. If they never write one, the knowledge leaves with them.
Red flags: a portfolio of demos with no users, and a first instinct to propose a multi-agent platform before understanding your operations. Anthropic, december 2024 advises starting with the simplest approach and adding complexity only when needed, which is a good test of judgement.
#When should you hire in-house, and when should you bring one in?
Hire in-house when several AI workflows are planned or running, a senior technical leader will manage the hire, the engineer can get data access without an internal fight, and AI is part of your product. The trade-offs are set out in Stennir vs hiring in-house.
Bring one in as a service when you need the first workflow running and do not yet know how much AI work you will have. The runbook from that work becomes the onboarding document for the hire you make later.
Be honest about the cases where you need neither. If nobody has agreed what to build, a consultant comes first. If staff only need to draft emails and summarise documents, a well-governed ChatGPT or Copilot plan with training may be enough.
#What should the first assignment be?
One workflow that matters to an operations team and is blocked by integration rather than ideas. Many pilots never reach production: Gartner, july 2024 predicted 30% of generative AI projects would be abandoned after proof of concept.
- Name the workflow and the manager who owns it.
- Record a baseline: volume, handling effort and error rate today.
- Agree a written spec: what the automation reads, what it cannot touch, and who approves its output.
- Decide where data is hosted before any build starts.
- Define done as running in production with real users, plus a runbook your team can operate.
#Where does Stennir fit?
At Stennir, a forward deployed engineer is a senior engineer embedded in your team during AI implementation. They map the workflow with the people who run it, build it into your systems with a person approving the output, and hand over: code in your repository, a runbook and a trained team.
It is the as-a-service route above. You pay for finished work, and scope and terms are agreed in writing before any work starts.
We are
Stennir embeds a senior engineer in your team to build one workflow into your systems and hand it over, so a later in-house hire inherits working software.
We aren't
Stennir is not a recruiter or a staffing agency, and does not place engineers on your payroll.
#What should a head of operations do next?
Write down the workflow you would give an engineer first and who owns it. If you cannot, read should you hire an AI engineer or work with an AI company and the examples in AI for operations. Then take the free readiness assessment or book a 30-minute call.
#Common questions
What job title should we post?
The title attracts people who know the role and people chasing the trend. Add the workflow, the systems and the languages to the post, for example Odoo, Zendesk and Arabic documents, so candidates can tell whether they have done this work before.
What do you need from us if we bring one in?
A named owner for the workflow, access to the systems and data in your own accounts, a person who approves AI output, and a place in your team's working rhythm. Without access and an approver, even a strong engineer ends up building a prototype that never reaches production.
Who owns the code an embedded engineer writes?
You should. Insist that the code sits in your repository, the accounts are in your name and the runbook is handed over. At Stennir that is written into the terms before work starts, so an in-house hire or another partner can take over without moving anything.
Does the engineer need to read Arabic?
Not always, but they must be able to test Arabic output properly. Ask them to explain how they would build a test set from your own Arabic and mixed-language documents, and who on your team would check the results. Stennir supports Arabic and English fully, with other languages on request.
