Forward deployed engineers
A forward deployed engineer in your team next week
Hire a vetted AI and data engineer from Involabs who works inside your tools, your standups and your customer environments. Onboarded within a week, billed monthly from about US$4,000, and backed by our founders and engineering practice.
Technology we use for this work
The problem
The engineer you need is the hardest one to hire
Forward deployed engineers sit between the model and the business. They take a vague request from an operations lead, turn it into a working system on messy real data, and stay until it holds up in production. Few people can do both halves well, and in-house hires for the role commonly cost well over US$100,000 a year before recruitment fees and a three to six month search.
Most teams do not need that commitment to get started. They need one capable engineer, quickly, who already knows how to ship AI into regulated environments. That is what we provide: our engineers, on monthly terms, working as part of your team.
What they do
Where a forward deployed engineer helps
Vetted AI and data engineers embedded in your team within a week, from about US$4,000 a month.
Turn a demo into a production system
Take a prototype, a notebook or a vendor proof of concept and make it reliable: typed contracts, retries, evaluation, tracing and a deployment your team can run.
Integrate AI with the systems you already have
Connect models and agents to your databases, CRM, ticketing, document stores and internal APIs, with read-only access unless a write path is designed and approved.
Build retrieval and agent workflows
Retrieval over private documents, natural language to query, and multi-step agents with human approval where an action has consequences.
Fix the data underneath
Pipelines, schema contracts and quality checks for the sources the use case depends on, so the model is not blamed for a data problem.
Work with your customers on site or remotely
Join customer calls, scope requirements with business users, and deploy into the customer environment under your brand when you are a product company scaling delivery.
Leave it maintainable
Code in your repositories, documentation written during the work, and a handover your team can operate without us.
How hiring works
From first call to first commit in a week
-
Day 1
Scoping call
- Your stack and use case
- Skills and seniority needed
- Working hours and access
-
Days 2 to 3
Matched profiles
- One to three engineers
- Relevant past work
- Availability confirmed
-
Days 3 to 5
Your interview
- Technical conversation
- Live problem on your context
- You choose
-
Within a week
Onboarded
- NDA and access set up
- Joins your standups
- First goals agreed
-
Monthly
Review and adjust
- Review against goals
- Scale up or down
- Swap if the fit is wrong
Pricing
Engagement options
Dedicated FDE
From about US$4,000 a month
One engineer, full time, embedded in your team and reporting to your lead.
- AI, data or full-stack profile
- Your tools, repos and standups
- Monthly rolling terms
- Founder escalation path
FDE pod
Quoted per scope
Two to four engineers with a senior lead, for a larger program or several customer deployments at once.
- Mixed AI, data and platform skills
- Senior lead who owns delivery
- Shared evaluation and tracing practice
- Scale between months
- Engineers vetted by our founders through technical interviews and review of shipped work
- Mutual NDA before any data or system access
- All code, infrastructure and documentation in your accounts from day one
- Access granted by you and revocable by you at any time
- A written progress update every week
- A replacement engineer if the fit is not right
- No recruitment fees and no long-term lock-in
Track record
Work our engineers have shipped
An AI compliance platform for Saudi PDPL, live with banks
A platform that reviews client documents against the Saudi Personal Data Protection Law, scores the gaps and drafts compliant replacements, now in production with banks and finance companies.
Result: 95% content fidelity on AI-drafted documents
Read the case studyConversational BI for teams with no data team
Connect a spreadsheet or database and come back to a dashboard that already means something, then reshape it by asking in plain language.
Result: 100% of model calls routed through one traced gateway
Read the case studyAn AI equity research platform that cites every claim
Enter the ticker of a US-listed company and the platform reads five years of filings, earnings call transcripts and market data, then writes a cited memo with growth signals.
Result: 100 names tracked with the same depth every quarter
Read the case studyContext
Industries and related services
Industries
Related services
FAQ
Forward deployed engineers: common questions
What is a forward deployed engineer?
An engineer who works directly inside a client or customer environment to scope, build and deploy production software, rather than building a generic product from a distance. For AI work, that means taking a real business problem and real data and shipping a system that works on them.
How quickly can an engineer start?
Usually within a week of the first call. We share matched profiles within three business days, you interview the engineer, and onboarding starts as soon as you choose and access is in place.
How much does it cost?
A dedicated forward deployed engineer starts from about US$4,000 a month, depending on seniority, skills and working-hours overlap. Pods are quoted per scope. There are no recruitment fees, and terms are monthly.
How are your engineers vetted?
Every engineer is interviewed by our founders, reviewed on systems they have actually shipped, and works within our engineering practice: evaluation sets, tracing, typed contracts and written handover. You also interview them yourself before they start.
Who owns the code and IP?
You do. Work happens in your repositories and cloud accounts, under an NDA, and everything the engineer produces for you is yours.
How is this different from a freelancer or staff augmentation?
The engineer is part of Involabs, not an anonymous marketplace profile. Our founders stay accountable for the engagement, the engineer can draw on the rest of our team for specialist questions, and we replace them if the fit is not right.
Can we scale up, scale down or stop?
Yes. Engagements run month to month. You can add engineers, move to a pod, or end the engagement with notice agreed in the contract.
Tell us the role and the start date
Share the stack, the use case and the skills you need. We come back with matched engineer profiles within three business days.