Assemble a senior AI team in days
Senior, AI-ready builders matched to your stack and embedded with a lead. Skip the hiring cycle and start building this week.
<2%
acceptance rate
11,000+
vetted builders
300+
companies
When one hire isn't the answer
Jason M.
Product Manager
10 Years Experience
Angela W.
ML Engineer
8 Years Experience
Ben W.
Data Scientist
10 Years Experience
Ana P.
Product Designer
9 Years Experience
How A.Team's tech recruitment process works
You scope the build
One conversation on what you're shipping, the stack, and the shape of team it needs.
We match the team
AI-powered matching against a network of 11,000+ senior builders returns a group tuned to your problem: the disciplines you need, a lead to run delivery, sized to the work.
You kick off in 48 hours
The team is assembled and working within two days of sign-off, embedded in your tools and your standups.
You scale as the work changes
Add builders for a push, scale back when it ships. The team bends to the work rather than the other way around.
The team you assemble
Every AI build needs more than engineers. We staff the roles the work calls for and size the mix to your problem: ML engineers, data engineers, AI/ML architects, MLOps engineers, data scientists, product managers, and a delivery lead who owns the plan. You get the composition your build needs, not a generic pod.
Trusted by 300+ companies
What your team ships
Senior, AI-ready builders doing custom AI development in production, not demos. The team covers the full surface an AI build needs. Built in the stacks your team already uses: Python, PyTorch, TensorFlow, and the major model families. Teams have shipped across CPG, retail, fintech, healthtech, media, and SaaS; the domain bends to your build.
AI & Data
LLM integration and fine-tuning, RAG, and multi-agent systems. Built to run in production against real users, not to demo in a notebook.
Data and MLOps
The data engineering, pipelines, and analytics underneath the models, plus the MLOps to deploy, monitor, and scale them as usage grows.
Multimodal and computer vision
Vision, speech, and multimodal systems for the builds where text alone isn't the problem.
The product around the model
Full-stack, mobile, and cloud infrastructure, so the AI ships as a working product rather than a proof of concept.
Shipping something bespoke?
We can help. Our matching team scopes custom teams regularly.
Teams we've stood up
Apprentice
Rebuilding a Pharma Platform in 45 Days to Distribute 370M Life-Saving Vaccines
BlankStreet
Creating a Digital Ordering System that Fueled 40 New Locations in Three Years
Endeavor
Building Olympic-Scale Customer Support Infrastructure in 30 Days.
The A.Team difference
Teams run hourly, contract-to-hire, ongoing, or advisory, and you move between them as the work shifts. Scale up for a sprint, scale down when it's shipped. No scope lock-in. Builders set their own rate, you see one all-in number with no setup, placement, or retainer fees, and no hidden markups. And if a builder isn't the right fit, we replace them in days, not weeks.
A lead runs the team, owns the plan, and keeps the code maintainable. On longer engagements, builders who know your system grow into that lead role themselves.
If what you actually need is senior individual contributors doing the work, that's exactly what you get. If you need someone owning the whole delivery, that's there too. The model scales with how much ownership you want to hand over.
A.Team gives you senior builders who clear a bar under 2% get past, matched to your stack, working in your timezone and inside your workflow. They read as part of your team because they're operating like one. And where most dedicated-team shops quote two to four weeks to start, we kick off in 48 hours.
Every team can draw on A.Team's CxO network, senior operators who've built and scaled before, for the strategic layer above the build.
Featured guides
View all
Contractor vs. FTE: Total cost of ownership
A complete total cost model for comparing contractors to full-time employees. Covers employer payroll tax, benefits, overhead, ramp cost, and the breakeven point where each model becomes more cost-efficient.
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What a senior fullstack engineer costs in 2026
A senior fullstack engineer in North America in 2026 costs roughly $240K to $320K loaded as an FTE and $120 to $175 per hour as a contractor ($216K to $315K annualized at full utilization). Team augmentation engagements price to scope and team composition rather than a published hourly rate, so the useful budget question is total program cost over the engagement window, not rate alone. Hourly rates don't capture management overhead, ramp, and rework, which are usually what moves the total.
Read guide
What a senior backend engineer costs in 2026
Senior backend engineers on contract range from $90 to $200 per hour in the US market in 2026, with the upper range driven by specialization in AI inference infrastructure, distributed systems, and security-critical APIs. Mid-level contractors run $65 to $105 per hour. The platform you hire through determines how much of that hourly rate reaches the engineer versus how much goes to platform margin.
Read guide
How to evaluate senior-talent vendors
Twelve pages on how to evaluate senior-talent vendors. Ten questions for your next call, a six-dimension scorecard, and the cost math behind every decision.
Common questions about hiring through A.Team
Matching happens in days; most teams are assembled and kicked off within 48 hours of sign-off.
From a two or three person pod to a multi-team build across disciplines. The network is 11,000+ builders deep, so size follows the work.
Hourly, contract-to-hire, ongoing, and advisory. You can move between them as the project changes.
Under 2% of applicants are accepted. Every builder is senior, and AI-ready from day one.
You scale down. There's no scope lock-in and no penalty for resizing the team when the work changes.
Ready to build with a senior team?
Tell us what you're shipping. We'll come back with a team. No six-week scoping exercise. The right people, fast.