Nearshore AI Staff Augmentation
Tecla places vetted Latin American engineers into US AI teams, from LLM, generative AI, and MLOps specialists to the AI and ML engineers building around them. Under our EOR, screened for how they build with modern AI.
See the AI companies that build with us, what they say about us, and how a hire comes together.
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The engineers behind AI products
The AI engineers Tecla places have taken models into production, and know the gap between a notebook that runs and a service that holds up on real data.
That experience stays scarce. Engineers who have carried models from prototype to production, with the data and cost that come with it, are hard to hire on your timeline in the US.
Tecla brings them on in your time zone and in place within weeks. That is how the AI companies below built their teams.
From teams that scaled with Tecla
A few of the AI teams, the engineers they brought on, and what came of it.
Credo AI
“For a company defining a category in real time, the operational lift of cross-border hiring matters as much as the talent itself.”
Crux Analytics
“The team became active participants in technical discussions and feature delivery early, taking ownership of important components within the platform.”
Tell us the role and skip the sourcing and screening.
Why it tends to be a smooth fit
In your time zone
Engineers work with your team in real time, so model changes and releases move without an overnight handoff.
AI-fluency screened
Every engineer clears an AI-fluency layer in the vetting, so they already work with AI coding tools day to day and know where to rely on their own judgment.
Ships production AI
An engineer-to-engineer technical assessment checks real systems, from LLM applications and MLOps to agentic work.
Low risk to try
Every hire carries a 90-day replacement guarantee, though it is rarely called on. Retention runs 98%, and the engineers who learn your product stay for years.
Staff augmentation, in-house, or outsourcing
Three ways to add AI engineering capacity. Here is how they differ, and where staff augmentation fits.
Staff augmentation
- Vetted engineers join your team
- You direct the work and roadmap
- Employed under Tecla’s EOR
- Scale up or down in weeks
- You keep IP and continuity
In-house hiring
- You own recruiting and HR
- Full control, full overhead
- Hiring cycles run months
- Payroll and benefits on you
- Hard to scale down
Outsourcing
- Vendor owns a defined scope
- You track outcomes, not the team
- Less control over the day to day
- Good for a self-contained project
- Team leaves when the project ends
When staff augmentation fits an AI team:you have the roadmap and the standards, and you need vetted engineers who integrate fast, work your hours, and stay with the product, without the hiring cycle or the overhead of a full-time headcount.
Hire AI developers and engineers
Tecla staffs from foundation-model work to applied production, across the AI stack.
Roles
How hiring works
Share the role
Tell us the role, stack, and any compliance needs through your dashboard.
Review a shortlist
A shortlist of candidates who have cleared Tecla’s vetting, in as few as 3 days.
Interview
Meet the ones you like. You make the call, we coordinate everything.
They join your team
Employed under Tecla’s EOR, working in your time zone from day one.
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Build your AI team with Tecla
Tell us what you need and skip the sourcing, screening, and first-round calls. You'll meet a vetted shortlist in as few as 3 days.