Short answer: In the US, AI engineers typically earn $104K to $189K a year in base wages (the middle 50% of computer and information research scientists, BLS, May 2025), and the median works out to about $205K a year once benefits are added. In Latin America, Levels.fyi's 2026 data puts median total pay for machine learning engineers (the closest title with data across the region) between $42K (Mexico) and $46K (Brazil) among the countries with at least 10 submissions (Brazil, Mexico and Colombia).
AI engineers build products and internal tools on top of large language models: retrieval, agents, evaluation, guardrails and the integrations around them. The title is new, so salary data is thin.
We're Ryz Labs. Our senior engineers across Latin America work on US teams, so we look at these numbers every week. The market figures below are public data with their source and year. Ryz pricing (typically $7,000 to $15,000 per engineer per month) is covered below.
Salary sources measure different things, so we show the measure next to every figure. BLS surveys employers and reports base wages only. Levels.fyi collects self-reported total pay, including equity and bonuses, which pulls its numbers toward large tech companies. Get on Board reports after-tax monthly salaries from job posts, so its figures read lower than gross pay. Read each row on its own terms rather than comparing them one to one.
We flag Levels.fyi samples under 20 submissions. Brazilian survey figures are in reais, not converted. Other offshore rows cover all software engineers, because role-level data there is thin.
Seniority is the biggest single driver. In the US, base wages for computer and information research scientists run from $82K at the 10th percentile to $231K at the 90th (BLS, May 2025). Latin America shows the same pattern: Levels.fyi's 2026 medians for entry-level software engineers range from $9K to $32K across the five countries, while senior medians range from $45K to $63K. A senior engineer who can work without close supervision usually costs less in total than two juniors who need it.
AI engineering pay depends on how close the work is to production. Prototyping with model APIs is common; shipping an LLM-based system that handles real traffic, with evaluation suites, cost controls, security review and monitoring, is much rarer. Many come from back-end or ML backgrounds, and their pay tracks those markets. In Latin America, Levels.fyi has very few AI engineer submissions, so we use machine learning engineer data for the country comparison and show the AI engineer cells separately.
The same person costs different amounts depending on how you engage them. A direct hire carries salary, benefits, employer taxes and recruiting. A freelancer bills by the hour with no benefits, but you manage the work and the risk of them leaving. A staff augmentation firm charges a monthly rate per engineer that covers sourcing, vetting and replacement.
Overlap with your working day has a cost even when it does not show up on an invoice. Engineers several time zones away often wait a day for code review or answers, and that slows the whole team. Latin America shares most of the US working day, which is a big reason US companies hire there. Lower-cost regions with little overlap can end up costing more in lost speed.
Salary is not the full cost of an in-house hire. In BLS's June 2026 Employer Costs for Employee Compensation release, wages made up 68.5% of total compensation for private-industry management, professional and related workers, and benefits made up the other 31.5% ($24.82 an hour on top of $54.06 in wages). That is why we divide salary by 68.5% to estimate a fully loaded figure. On top of that come costs public data does not price well: the weeks a seat sits empty while you recruit, interview time from your engineers, onboarding, equipment and software, and the management time every hire needs.
There are five common ways to bring on AI engineers. Each has a different cost structure, so the right comparison is total cost for the work you need done, not the headline rate.
Some providers publish their own figures. These are their claims, not ours, and we have not verified them. Arc's 2026 guide, based on a survey of its freelancers, puts typical hourly rates at $35 to $75 in Latin America and $82 to $130 in the US and Canada (Arc). BairesDev says nearshore development typically runs 30 to 50% below US rates (BairesDev). Howdy, drawing on its own salary data, puts Latin American software engineer salaries at $55,000 to $67,000 and its all-in cost at $65 to $72K a year (Howdy).
Ryz typically charges $7,000 to $15,000 per engineer per month, mostly for mid-level to senior people. Mid-level engineers (comparable to Amazon L5, SDE II) typically cost $7,000 to $10,000 monthly; senior engineers (comparable to Amazon L6, Senior SDE) $10,000 to $15,000 (Levels.fyi total pay, October 2026: L5 $253K to $364K; L6 $350K to $523K+, top package above $500K). Lead engineers start at $15,000 a month, quoted per team; for junior roles, ask us for a quote. Every engagement is a custom quote, scoped per team. Our senior Latin American AI engineers (only the top 1% of the engineers we interview make it) work on your team, on US business hours. For AI work, we also run AI pod teams that build in your cloud and repos.
See how we hire AI engineers, how staff augmentation with Ryz works, or model your own numbers with our talent cost savings calculator.
Market pay is the floor, not the price. Levels.fyi's 2026 medians for machine learning engineers run from $42K in Mexico to $46K in Brazil. Get on Board's job-post data shows senior salaries offered across the region averaging $3,999 a month after tax. What you pay depends on how you engage them: a freelancer, a vendor or a direct hire each adds different costs on top of pay.
BLS reports a median hourly wage of $67.45 for computer and information research scientists (May 2025). With benefits, that is roughly $98 an hour to the employer. Freelance and agency rates are usually higher than the wage, because they cover the contractor's own taxes, gaps between projects and the agency's margin.
They overlap. ML engineers usually train and serve their own models. AI engineers more often build on top of foundation models (retrieval, agents, evaluation). Many roles now ask for both.
Less reliable than for older roles. The title is new, samples are small (especially in Latin America), and companies define it differently. Treat the figures here as directional and compare against ML engineer and back-end data.
All figures were checked on October 2, 2026. Ryz prices are typical ranges by seniority; your quote is scoped per team.
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