A.Team Deployed gives AI software companies senior, client-ready engineers who embed with your customer, carry your badge, and handle the last mile, in days rather than a hiring cycle.
AI software our engineers deploy
Partners
You closed the deal.Now you have to deliver it.
A.Team Deployed closes the gap without the headcount. Senior engineers deploy in days, embed under your banner, and own the work that turns a signed contract into a live deployment.
Senior and client-facing by default.
Sales outpaces delivery
Enterprise contracts close faster than deployment teams can staff them, leaving signed deals waiting on people you don't have.
Demand doesn't arrive evenly
Deployment load lands deal by deal, not on a hiring plan. A team sized for your best quarter sits idle in the next one, and a team sized for the average can't cover the peak.
The last mile stalls everything
The product works in the demo. Legacy data, compliance review, internal workflows, and change management are the customer-side work no vendor can absorb permanently.
Senior FDEs are scarce
The forward deployed engineer role grew roughly 40x in 24 months, and demand for senior FDEs far outstrips supply.
The scarcity has a shelf life
Enterprises are building the capability in-house, agents are starting to self-deploy, and in two or three years this gap closes. A permanent org is a long answer to a temporary problem, and most mid-market AI companies can't justify one anyway.
What A.Team Deployed gives you
Ramps with your pipeline, not your payroll
Bring on a dedicated engineer when a deal closes, step them down when it wraps. Sized to what your customer needs this quarter, not a permanent hire you're carrying between deals. Still under your brand, still on your stack.
Cultivated over years
Deployment-ready engineers drawn from a deep AI bench and assessed across 8 dimensions for fit to your deployment. We've been developing this profile since before it had a title.
They see it through, then hand it back
Your engineer builds the last mile and stays through handover, not rotating off mid-delivery. Embedded with your customer day to day, they're often first to spot the next expansion.
Priced against the delivery
Monthly, per engagement, sized to the delivery your customer is expecting. No placement fees, no severance, and no permanent org to justify once the rollout is done.
What we see before you do
Every engineer is scored before they make the bench: across production AI experience, ownership, client-facing communication. Deployment-ready engineers come out of our network with real depth in the industries and disciplines enterprise rollouts land in.
Engineers, AI architects, data scientists, product managers and DevOps.
Build
- Craft depth91
- Production maturity88
Deliver
- End-to-end delivery86
- Scoping & judgement82
Systematize
- Reusability & product mindset79
Land
- Communication74
- Adoption & impact85
- Enterprise & SaaS fluency58
Illustrative. Real builders are scored the same way; we don't publish individual scores.
Who you get, and where they've worked
- Roles
-
- AI architects
- Engineers
- Data scientists
- Product managers
- DevOps
- Domains
-
- CPG
- Legal & professional services
- Healthcare
- Financial services
- Manufacturing
- Pharmaceuticals
- Civil & environmental
- PE / VC
How it works
You brief us on the engagement
One call on the customer, the scope, the stack, and the timeline. We map your delivery commitment to the right engineer profile.
We scope it and name the team
Within three to five business days we come back with the engineer or pod we're putting on it, priced, and why we're proposing that team. You meet them before anything starts.
They embed with your customer
Your matched engineer deploys under your banner and takes on the last-mile work.
They get it repeatable, then hand it over
Once the work is repeatable, the knowledge transfers to the team who'll run it and the engineer rotates off. The capability stays with your team.
What your deployed engineers handle
Roughly 70% of forward-deployed work is evals, custom pipelines and change management, and only 30% is core build, the inverse of traditional services. That's the part a contractor doesn't cover.
Legacy data
Migration and integration across legacy systems, internal APIs, identity and permissions.
Compliance & security
Security review and the procurement realities that stall a rollout.
Workflow integration
Internal workflow integration and custom configuration.
Change management
Customer-side change management and enablement.
Production hardening
Monitoring, failure handling, and the hardening a demo environment never surfaces.
Customer-specific evals
What "correct" means differs by customer. The engineer builds and tunes it.
Enterprise access
NDAs, IP assignment, and badge access, handled as standard.
Procurement cover
Your account team stays out of infrastructure and security negotiations.
Runbooks and handover
UAT, training, and the runbooks that let your team run it once the engineer rotates off.
The caliber of engineer your customer meets
Senior, client-facing builders from the same network that ships production AI for Fortune 500s and high-growth startups.
Snappt
From Single SKU to Multi-Product AI Platform in 6 Months
15%CORE PRODUCT GROWTH
D-ID
Launching a GenAI-Powered Mobile App That Hit 1M Downloads in Under a Year
5mo.MVP BUILD
Dicer.ai
Reducing Ad Creation Time from Days to Hours with AI-Powered Video Generation
95%Faster ad production
A.Team Deployed vs. the alternatives
How we compare to a permanent FDE hire, generic staffing, and your existing contractors:
| Criterion | Permanent FDE hire | Generic staffing | Your contractors | A.Team Deployed |
|---|---|---|---|---|
| Time to start | 6–9 months | 2–4 weeks | Bench-dependent | 3–5 days |
| Vetting | Internal | Self-reported | Unknown to you | Invite-only, under 2% |
| Client-facing readiness | Built for it | Rarely | Sometimes | Standard |
| Sees it through handover | Yes | Sometimes | Sometimes | Yes, same engineer |
| Cost | $200–350K/yr loaded | Opaque hourly markup | Variable | ~$25K/mo, transparent |
| Wears your badge | Yes | No | Sometimes | Yes, by design |
Guides for hiring forward deployed engineers
Forward Deployed Engineering
What a forward deployed engineer is, and how to spot a real one
What is a forward deployed engineer? Origin, what an FDE owns after the contract signs, FDE vs solutions engineer compared, and a test for vendors.
Forward Deployed Engineering
Build, rent or partner: When an AI vendor should hire forward deployed engineers
How to hire forward deployed engineers: in-house FDE team, rented senior FDEs under your badge, or an implementation partner. Decide by signal.
Forward Deployed Engineering
The eight things we score before an engineer meets your customer
The eight criteria we score before an engineer meets your customer, how the score is built, and what to ask anyone selling you FDEs.
Forward Deployed Engineering
How FDE teams are actually structured: Ratios, pods, reporting lines and the first 90 days
How an FDE team is structured: the published ratios, what a pod contains, where it reports and the first 90 days, compiled from public sources.
Frequently asked questions
Roughly $25,000 per month for a senior builder, fully loaded. Engagements are scoped to your customer's delivery commitment, so you pay for the work the project requires. Insight Partners puts a permanent in-house FDE at $200–350K a year fully loaded, so this is capital-efficient for engagements that can't justify a permanent function. No placement fees, no severance.
Ready to brief us on the engagement?
Tell us about the engagement (customer profile, stack, timeline) and we'll come back with named, senior engineers ready to embed.