What clients we have worked with say
“90% of the candidates they gave us were very good. A majority of the candidates found by Klyver have been a successful fit for the client. The team at Klyver is personable, open-minded, and communicative. Their flexibility makes them stand out.”
Interfactura“Their service was satisfactory and they responded in good time. Their responsiveness and excellent customer service resulted in a good workflow.”
OptimissaKlyver recruits and technically screens Data and AI talent in Mexico and LATAM for U.S. and Canadian companies. We charge a one-time placement fee — the client hires directly, as a contractor, through their own entity, or via an EOR of their choice.
The data and AI profiles in highest demand.
From data pipelines to production integrations with LLMs.
Data Engineers
Pipelines, ETL/ELT, Airflow, dbt, Spark.
Analytics Engineers
Data modeling, dbt, modern warehouses.
BI
Looker, Power BI, Tableau — dashboards for business decisions.
AI/ML Engineers
ML models in production, MLOps, feature stores.
LLM / GenAI
LLM integrations, RAG, agents, fine-tuning.
Data Science
Statistical modeling, experimentation, A/B testing.
A recruiting process, not an outsourcing template.
Klyver doesn't sell a development factory or run your payroll. We find and screen the professional; you decide how to hire them.
You define the role
Role, stack, seniority and compensation range. No volume minimums — start with a single position.
Sourcing and technical screening
We search across Mexico and LATAM, filter for real experience, and run technical screening before presenting anyone.
You receive evaluated profiles
A shortlist with concrete evidence of what the candidate can actually do, not just a resume.
You hire, directly
As a contractor, through your own entity, or the EOR you already use. Klyver doesn't sit in the employment relationship.
Placement fee
A one-time placement fee, quoted per role by seniority. No retainer and no recurring monthly billing per candidate. We send the proposal within 24 business hours. Replacement guarantee based on seniority.
Observed compensation
Two different markets, both checked on Sep 20, 2026. Pay for remote roles with US-facing companies is quoted in US dollars; the local Mexican market is quoted in pesos. They are not the same labor market, so do not subtract one from the other.
Remote roles with US-facing companies (annual salary, USD)
| Seniority | Annual salary | Employer cost (1.3 to 1.4 times) |
|---|---|---|
| Junior (0 to 2 years) | $24,000 to $28,000 | $31,200 to $39,200 |
| Mid-level (2 to 5 years) | $42,000 to $66,000 | $54,600 to $92,400 |
| Senior (5+ years) | $66,000 to $90,000 | $85,800 to $126,000 |
Source: Revelo, "How to Hire Software Developers Based in Mexico in 2026" (updated Jul 4, 2026; cites Glassdoor and Salary.com). General software developers; the source notes Mexico City and remote roles often carry a 10 to 25% premium. The multiplier covers IMSS, Infonavit, the mandatory year-end bonus (aguinaldo) and profit sharing (PTU) under formal employment.
Local Mexican market (average monthly pay, MXN)
| Title | Monthly average | Salaries in sample | Updated | Source |
|---|---|---|---|---|
| Data engineer | 20,459 | 143 | 2026-09-10 | mx.indeed.com |
| Data scientist | 19,531 | 103 | 2026-09-10 | mx.indeed.com |
Indeed Mexico publishes a single average per title and no range. Samples under 100 salaries are indicative only.
Frequently asked questions
Screening looks for evidence of real work: production integrations with LLMs, RAG architectures running in production, hallucination evaluation and mitigation, and cost/latency trade-off decisions — not just conceptual knowledge of the topic.
Yes. MLOps sits at the intersection of Data/AI and DevOps — we evaluate experience with training pipelines, model versioning, drift monitoring, and production deployment.
A Data Engineer is evaluated more on pipelines, orchestration, and data infrastructure. An Analytics Engineer is evaluated on data modeling, quality, and the semantic layer for business consumption. They're different screenings even though the tools overlap.
Yes. It's a common case: companies that need their first Data Engineer or Analytics Engineer to lay the foundation, without hiring a full team from day one.
We also recruit these profiles.
Software Engineers
Full Stack, Backend, Frontend, Python, Java, .NET, Node.js, React.
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