Senior AI developers and data engineers from Latin America, screened against the layer of your stack the role has to own.
Most teams hire AI developers after a feature has already been promised. The demo worked, the roadmap moved, and now someone has to run it against real traffic. The job description that follows gets written around the model, because the model is the part everyone saw.
What breaks afterwards is usually underneath it. Retrieval pulls a stale record, two dashboards disagree on revenue, or a training run turns out to be reading from a table nobody maintains. Hiring a second person who's good at models won't fix any of it.
So we keep two benches. Tell us what's breaking and we'll screen senior Latin American engineers against that layer, then send two or three scored profiles within days. You interview them and you decide.
Book a Free ConsultationEvery role below has its own screen and its own shortlist. If you already know the title you need, go straight to it. If you only know what's broken, tell us on the call and we'll match it to a role.
These roles own whatever produces the prediction, from the prompt in front of
it to the infrastructure serving it.
Teams hire data management engineers once the numbers stop agreeing with each other.
Everything your models and dashboards read from sits with these roles.
Every AI and data hire clears the same screen. Most of the effort goes into how someone reasons about a system they cannot fully predict, rather than what is listed on the CV.
Cultural match, technical match, English in live conversation and interpersonal skills, each scored 0 to 5. We read the whole card instead of a cutoff number, and you see it.
A top score goes to someone who leads the conversation when it helps, listens when it does not, and says plainly where their knowledge ends. That last part counts for more here, since most of the tooling is new enough that nobody has years behind them on it.
We score how a candidate walks through something they have built and run against real traffic. A take-home result never sets the technical score.
Whiteboard walkthroughs are the default on development roles. Data engineering gets a real exercise instead, because the work is concrete enough that doing it tells us more than diagramming it.
Even on mid-level roles we look at how someone plans their week, how clearly they write, and how fast they settle into a cross-functional team.
We understand the industries we serve. That is why we know which hires would fit perfectly to your team.
Mubeen Ibrahim, Head of Data, Superbalist. Five-star review.
Deverr has done a great job of meeting and exceeding our expectations. What stands out about Deverr is their engineering team's ability to work efficiently without compromising quality.
Deverr built our ingestion and data modeling engine for Shopify data. They built rock-solid infrastructure, were professional, and responsive. True partners in every sense.
We needed a senior full-stack developer fast. Deverr placed someone in under two weeks who was shipping code by day three. Six months later he's one of our core team members.
We couldn't be happier with the full-stack, AI, and WordPress developers Deverr found for us. They saved us a ton of time recruiting and brought in highly experienced developers who fit our culture perfectly, at a fraction of what we'd pay for U.S. developers of the same skill level. 5 stars, I can't recommend them enough.
Alvis.Care started as my garage project, built on Lovable, held together by vision and duct tape. Within a month of bringing on Deverr, they placed Allan as our lead engineer and our code was professionalized and stabilized. Allan took ownership of the team and gave me back time to sell the vision. If you built something real and need it to become a company, this is how you do it.
Deverr is officially the gold standard for scaling a team without the usual headaches. We will never go back to traditional recruiting after seeing how effortless this was.
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Expect 30 to 50% below a comparable US hire. One monthly rate covers salary, benefits, payroll and local compliance, with no recruiting fee on top. We'll give you the real number on the call once we know the role and the seniority.
If the model already exists and the trouble is what happens around it, prompting, retrieval, guardrails, evals, that's an AI engineer. If the trouble is the model itself, training, serving, monitoring, retraining, that's a machine learning engineer. Describe the symptom on the call and we'll name the role.
Seven days on average from the first call to their first day, and you'll see two or three scored candidates within days of the consultation.
Senior only. Every brief we screen against asks for five or more years in the discipline, and we don't place juniors on either bench.
We do, in their own country, payroll and benefits and local compliance included. Your vendor review covers Deverr as a staffing partner, so there's no new legal entity in a new jurisdiction to approve.
Fill in the form below and you'll go straight to our calendar to pick a time. Here's what happens next:
