AI-Ready Staff Augmentation
Not AI engineers. Vetted full-stack, backend, and frontend developers fluent in Copilot, Cursor, Claude, and ChatGPT. They use AI as a tool, not a crutch. 30 to 50% faster delivery, same code quality.
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Avg delivery speed-up
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To first shortlist
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Of applicants pass vetting
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Engineers placed
What it is
AI-fluent staff augmentation means hiring developers who already use AI tools well as part of their daily workflow. They're not AI engineers. They're full-stack, backend, frontend, and mobile developers who ship faster because they know how to use Copilot, Cursor, Claude, and ChatGPT for code generation, refactoring, debugging, code review, and documentation. AI fluency is one of the five dimensions we vet on, alongside technical depth, communication, ownership, and cultural alignment.
If you want someone to build an AI product for you (training models, RAG pipelines, LLM integrations), look at our AI services or our ML engineering roles instead. This page is about something different: regular developers who happen to be 30 to 50% faster because AI is part of how they work.
You want faster delivery without growing headcount
Your existing team already uses AI tools
You want a pairing partner for senior engineers
You're integrating AI tools into your dev process
You want someone who'll mentor your team on AI
You want to build an AI product
You need data scientists or NLP specialists
You don't have a code review process yet
You're trying to replace developers with AI
What you actually get
Not magic. Just the compounding effects of having engineers who use AI tools as a natural part of how they ship.
Boilerplate, tests, refactors, and integration glue: AI handles the rote work while the engineer reviews, validates, and ships. Same code quality, less time per task.
AI explains unfamiliar codebases, traces stack frames, and helps engineers ramp on legacy systems faster. Onboarding cycles shrink from weeks to days.
AI-assisted reviews catch obvious issues, missing tests, and inconsistent naming before you do. Engineers focus their cognitive budget on architecture and trade-offs.
Comments, READMEs, ADRs, runbooks: AI drafts them, the engineer edits for accuracy. The chronic 'we'll document it later' debt actually goes down.
We vet for the ability to catch when AI is wrong. Hallucinations, made-up APIs, incorrect type signatures: a fluent engineer notices fast. AI accelerates them, not the other way around.
AI is a step in their workflow, not a stop. They know when to reach for it, when to skip it, and how to keep their judgment in the loop. No 'vibe coding' anti-patterns.
How we vet
AI tool fluency is one of the five dimensions we vet every engineer on. Here's how we check it. The 5% who pass all five make it to your shortlist.
Which AI tools they use, for how long, and what for. Not just Copilot. We map their actual workflow: Cursor for refactors, Claude for architecture conversations, ChatGPT for unfamiliar APIs, etc.
We watch them solve a real-ish problem with AI on. How they prompt, what they accept blindly, what they push back on, where they catch hallucinations. The signal is in the friction.
We hand them code an AI generated with a subtle bug. Can they spot it? Do they validate type signatures, edge cases, and assumptions? This is the one most companies skip.
Is AI a stop or a step in their flow? Are they finishing tasks, or just generating code? We look for engineers who use AI to compound their judgment, not replace it.
The process
Same engagement model as our standard staff augmentation. The difference is in who you meet: every profile is vetted on AI fluency, day one.
Step 1
Share the role, stack, seniority, and how AI tools fit your team. A 30-minute call is enough. We confirm the AI tooling on your side (Cursor team plan, Copilot Business, etc.) and what's in scope for the engineer.
Step 2
You receive 3 to 5 pre-vetted profiles within 3 days. Each profile shows the AI tools the engineer uses day to day, the work they've shipped with them, an English communication assessment, and a video introduction.
Step 3
You interview the engineers you like. Pair on a real task with AI tools on. Watch how they prompt, validate, and integrate output. We don't gate-keep the format; the engineer is briefed on your stack and AI tooling first.
Step 4
Once you say yes, the engineer signs on, gets access, and joins your sprint cadence. We help with the AI conventions playbook so the engineer matches your team's standards (linting, prompt patterns, what AI is and isn't trusted with) from day one.
Step 5
If you want more AI-fluent engineers later, we move faster (we already know your stack, your tooling, and your AI conventions). If something isn't working, we replace within 30 days at no cost. Most clients stay 12+ months.
FAQ
Related
The five dimensions we vet on. AI fluency is one. The others are technical depth, communication, ownership, and cultural alignment. Why all five matter.
ServiceThe main service. Vetted engineers join your team and follow your direction. AI fluency comes built-in across every placement we make.
AI ServicesDifferent page for that. ML engineering, RAG pipelines, automation, computer vision, NLP. If you want a delivery team for AI itself, start here.
Ready to ship faster?
Tell us the role, stack, and AI tools your team uses. We'll send 3 to 5 vetted profiles within 3 days. AI fluency vetted, no premium.
