Hire senior AI developers.

Vetted AI talent matched in 72 hours. Transparent per-builder pricing. Working builder embedded in two weeks under your team's day-to-day management.

$130+/hr

Senior US AI contractor starting rate

72 hrs

From scoping call to curated shortlist

~2 weeks

From scoping call to working builder

3-to-5 months

Typical FTE search timeline for a senior AI engineer. By the time the hire is closed, the model landscape has shifted.

We had a shortlist of AI engineers. All of them had built demos. None of them had shipped a system that survived contact with production traffic. The two things are not the same.

When to bring in a senior AI developer

The clearest engagements have an AI system to build, not a buzzword to chase.

An LLM-powered feature that has to ship with an evaluation loop, not just a prompt. A RAG system that needs retrieval quality before it needs more documents. An agent that takes real actions in a product workflow and has to fail safely. A model-cost model that has to land before the bill becomes a board topic. Senior AI work in 2026 isn't 'use ChatGPT in our product.' It's deciding when to retrieve versus fine-tune, when an eval framework matters more than another prompt, when the architecture itself determines whether the system is debuggable in six months.

The usual approaches

What most teams try

Hire on tool familiarity (LangChain, specific models)

The tools change too fast for a tool match to mean anything in six months. The candidate who's used LangChain isn't necessarily the candidate who can ship reliable AI systems when the framework shifts.

Filter for demo experience, not production shipping

Demos and production AI are different engineering problems. Cost-per-inference, eval loops, graceful degradation, and model drift detection are the things demos skip. They're also the things that determine whether the feature survives.

Scope 'an AI engineer' without specifying the AI system

LLM integration, RAG, agents, and fine-tuning select for different subtypes. A vague scope produces a shortlist where everyone looks qualified and nobody is actually a fit. The mismatch surfaces in month two.

Our approach

What A.Team brings

Vetted senior AI talent under your team's management. Transparent rates. Team Success layer for engagement health.

Senior AI talent, vetted at the seven-plus year band

Seven-plus years professional engineering experience (average eight to twelve). Six-stage vetting including guild peer review. Production AI judgment is part of the rubric, not just framework recall.

Curated shortlist in 72 hours, not 72 days

Typically three to four senior builders matched to your AI system, your production constraint, your timezone, and your rate band. You interview. Working builder embedded by Week 2.

Per-builder rate stated on every Service Order

One rate per builder on the Service Order, no hidden tiers or success fees. Procurement-ready.

The process

Three steps from scoping call to embedded builder.

Day 0: Scoping call

A 30-minute call to understand the work, the timezone, the rate band, and the engagement shape. No JD required.

Day 3: Curated shortlist

A curated shortlist (typically three to four senior builders) matched to your scope. You interview, you select.

Week 2: Builder embedded

Selected builder starts under your team's management. Team Success contact runs kickoff and stays close throughout.

Ready to scope an engagement?

Get a shortlist
What they deliver

Senior AI work covers four engagement archetypes.

LLM and RAG integration

Building production systems on top of foundation models. Retrieval pipelines that return useful context, not just nearest neighbors. Prompt chains designed for the failure mode, not just the demo path.

Agent system design

Agents that take real actions in real workflows. Tool design, action validation, human-in-the-loop checkpoints, and the fallback behavior when the agent reasons wrong. The architecture that lets the system be debugged when it misbehaves.

Evaluation framework engineering

Defined metrics, dataset of test cases, and the deploy-time check that catches regressions before they reach users. The infrastructure that turns 'is it working?' into a number the team can act on.

AI architecture

System-level design for AI-native products: which components are model-driven, which are deterministic, how the architecture survives a model swap. Architecture engagements typically run three to six months of intensive design work, then transition to an implementation team.

~2 weeks

Scoping call to working builder

Across recent senior AI engagements, the median time from scoping to embedded builder is about two weeks. FTE searches average three to five months, longer for architect-tier roles.

How we run onboarding
5–15%

Monthly retainer savings vs hourly

Monthly retainers run 5 to 15 percent below the equivalent hourly cost at full utilization and lock in builder availability.

AI engineer rate breakdown
$20K

Conversion fee floor for direct hires

If a contractor converts to FTE, the fee is the greater of $20,000 or three months at the monthly rate plus 10 percent. Published, not embedded.

Contractor vs FTE TCO
Enterprise ready

Procurement, security, and engagement governance built in.

MSA + per-builder Service Order

Standard A.Team commercial structure. Hourly or monthly rate per builder. No managing partner fee.

Net-15 invoicing

Standard MSA terms. One rate per builder on the Service Order, no hidden tiers or success fees.

Team Success layer

Named contact runs kickoff, checks engagement health, owns escalation. Not a managing partner; a Team Success contact.

Re-match if a builder isn't fitting

Team Success scopes a re-match against existing engagement context. No separate trial-period contract required.

IP assignment from day one

Standard work-for-hire language in every Service Order.

Global builder pool, regional matching

Senior builders across the US, Western Europe, and select nearshore markets. Matched to your timezone and rate band.

Skip the 3-to-5-month FTE search.

A.Team matches vetted senior AI developers in 72 hours at transparent per-builder rates.

RATES BREAKDOWN

AI engineer rates in 2026

Full rate breakdown for senior AI engineers, data scientists, and AI architects. Covers the AI premium, specialization tiers, and the hidden costs (inference, tooling, mis-hire) most rate comparisons miss.

Read the rates guide
HIRING DECISION

How to hire an AI engineer

The decision framework for scoping a senior AI hire. System type, evaluation rubric, ramp expectations, and the common failure patterns.

Read the guide
FAQ

Common questions about hiring AI developers through A.Team

Senior US AI engineer contractors run $130 to $200 per hour. Senior data scientists run $150 to $200. ML specialists (model training, fine-tuning, production ML systems) run $175 to $250. AI architect or CPO/CTO-tier engagements run $200 to $225 per hour, with top-of-network specialty architects above that ceiling. The AI premium over equivalent-seniority general engineering is real: roughly 15 to 30 percent on contractor hourly, widening further at the architect tier where supply is most constrained. Monthly retainers run 5 to 15 percent below the equivalent hourly cost at full utilization. Offshore senior rates run materially below the US bands, with the time-zone trade-off.

An AI engineer builds the components: LLM pipelines, RAG systems, agent workflows, evaluation loops. An AI architect designs the system structure: which components are AI-powered, how the data flows, how the architecture survives a model swap. Most teams need an AI engineer. Teams standing up a new AI-native product or remediating an existing AI system that's hard to maintain often need both, sequenced.

Time from scoping call to shortlist: 72 hours. Time from scoping call to a working builder embedded in your team: roughly two weeks, depending on scope confirmation and your interview cadence. Architect-tier engagements sometimes take an additional week to match given the narrower pool.

Vetting screens for it. The rubric includes production failure-mode walkthroughs, cost-per-inference questions, and evaluation-loop design conversations. The signal we're filtering on is whether the candidate has shipped an AI system that survived contact with production traffic, not whether they've built a portfolio demo.

Yes. The conversion fee is the greater of $20,000 or three months at the monthly rate plus 10 percent. The structure is published in the master agreement.

Your team. A.Team's Team Success contact runs kickoff, checks in regularly throughout the engagement (cadence set with your team), and is the escalation path. There is no managing partner layer on standard team augmentation engagements.