How Enterprises Can Scale AI Engineering Teams by Hiring in LATAM

The demand for AI engineers is outpacing supply in nearly every established tech hub. According to Secondtalent, there are 1.6 million open AI positions globally, but only 518K qualified candidates.

Over the past five years, Latin America has produced a meaningful and measurable cohort of AI engineers, trained through a combination of regional universities, Coursera's free and paid programs, and industry bootcamps with strong employer connections. Yet most enterprise talent acquisition teams still treat LATAM as a market for nearshore software development generalists rather than a source of specialized AI talent.

In this article, we’ll outline why LATAM’s AI engineering talent pool presents significant opportunities, the top eight countries to consider, and how to navigate the compliance risk of hiring across multiple countries.

Why LATAM's AI engineering talent pool deserves attention now

The AI and machine learning engineering community in Latin America is growing faster than comparable tech communities in Eastern Europe or Southeast Asia, with a talent base concentrated in a handful of markets that combine university output, industry demand, and English fluency. According to Coursera's 2025 Global Skills Report, Latin America recorded a 425% increase in generative AI course enrollments.

Multiple factors are driving this trend. First, world-class technical universities in São Paulo, Buenos Aires, and Monterrey are producing computer science graduates at a rate that local employers have yet to fully absorb, creating an opening for international teams willing to hire across borders.

Second, remote work normalization during and after the pandemic created a generation of LATAM engineers who are accustomed to async collaboration with North American and European teams, reducing the onboarding friction that historically made timezone mismatches a genuine obstacle. Third, many businesses leverage compensation arbitrage to optimize operational costs.

None of this means hiring in LATAM is simple or risk-free. The talent pool is real, but it is concentrated. Not every country in the region offers the same depth, compliance simplicity, or English proficiency.

The top LATAM markets for AI engineering talent

Choosing the best LATAM market for hiring AI engineers involves evaluating qualified talent, compliance complexity, and average compensation. We’ve outlined the top eight LATAM countries with the highest opportunities.

Brazil

Brazil offers significant talent pool depth compared to other LATAM countries. São Paulo is Latin America's most established AI engineering hub, home to over 700,000 developers strong in fintech, AI, and enterprise software development.

Compliance complexity is moderate, as engaging contractors and employees requires careful classification and local tax compliance. Factors like 13th-month salary and severance fund (FGTS) contributions add cost and administrative overhead that enterprises should factor into total compensation planning. Compensation arbitrage relative to the US is strong, particularly for mid-to-senior machine learning engineers.

Mexico

Mexico ranks among LATAM's top AI markets, with $18 billion in data center investment projected through 2030, reflecting the country's growing strategic importance as a regional AI hub. Tech hubs in Mexico City and Monterrey supply a strong pipeline of AI and engineering talent, anchored by institutions like Tecnológico de Monterrey, ranked #1 in Mexico and #4 in LATAM.

In a market where 100% of Mexican CEOs now identify AI as their primary driver of profitability, this reflects deep and growing enterprise demand for specialized talent. Regarding compliance, Mexico currently has no dedicated AI law in force. A Federal Law Initiative for the Ethical, Sovereign, and Inclusive Development of AI was published for discussion in April 2025 but is not yet enacted, meaning enterprises face fewer binding restrictions than in more regulated markets. Combined with US time zone proximity and competitive digital infrastructure, Mexico is a strong candidate for enterprises looking to scale AI engineering teams in LATAM.

Argentina

Argentina ranks third overall. UBA ranks #84 in the QS World University Rankings 2026 and produces engineers with the mathematical and statistical depth that AI and ML roles demand. Argentina also ranks highly for data science skills and English proficiency, making it one of the strongest markets for senior, specialized hiring. There’s a talent pool of over 115,000 software engineers, and compensation benchmarks are significantly below US equivalents with Argentine AI engineers averaging between $37,500 to $60,000 per year. Contractor compliance requires careful attention given Argentina's complex labor law framework.

Chile

The 2025 Global Innovation Index ranks Chile as the most innovative economy in Latin America. Its developer pool of approximately 61,000–66,000 professionals includes high expertise with 45% operating as senior developers. This creates notable opportunity for enterprises prioritizing seniority over volume. English proficiency is moderate, with Chile ranking 54th globally on the EF English Proficiency Index, sufficient for effective collaboration with North American teams at the senior level. Compliance complexity is moderate and manageable, though Chile's evolving labor reforms (including phased reductions to maximum working hours through 2028) mean contractor engagements require careful structuring from the outset.

Colombia

Colombia has emerged as a leading talent hub with a developer community of specialized professionals across a variety of technology companies. It boasts 2,126 active companies and $513 million in growth capital.

Bogotá and Medellín are two primary hubs. Bogotá accounts for over 50% of Colombian startups, and Medellín's Ruta N innovation district has built a growing ecosystem of generative AI and LLMs. Government investment is also accelerating the market through MinTIC's ColombIA Inteligente programme, which is actively funding applied AI research and development across the country. English proficiency at the national level is moderate, but within the senior tech talent market in Bogotá and Medellín, it is significantly stronger. Additionally, Colombia's timezone makes it one of the most practical nearshore options for North American enterprise teams. Compensation benchmarks are competitive, and the combination of a fast-growing talent base, government-backed AI infrastructure, and strong timezone alignment makes Colombia an increasingly compelling market.

Peru

Peru is a rich market for hiring AI engineers with 65,000+ IT professionals and 25,000+ tech graduates per year. Senior developers earn an average salary between $55,000 - $100,000, and Peru ranks #52 on the EF English Proficiency Index. AI adoption is growing in Peru, but political instability and cumbersome government procurement processes present challenges to the business environment. However, with its growing AI talent base and opportunities for scale, Peru is still a good opportunity for enterprise teams looking to hire AI engineers beyond the most established LATAM markets.

Ecuador

Ecuador is a growing market for enterprise AI hiring, classified by CEPAL's Latin American AI Index 2025 as a regional "adopter”, showing steady progress while navigating gaps in research and innovation. Significant infrastructure investment is accelerating that trajectory. In January 2025, the National Corporation of Telecommunications signed a five-year, $300 million partnership with Google, alongside new market entries from AWS, Oracle, and Starlink. This is expanding the technical environment in which local engineers work and upskill.

Additionally, Ecuador's regulatory posture is proactive. In 2025, the OECD introduced an AI Code of Ethics, signaling a governance-forward approach to AI usage. Ecuador also won the IDB's 2025 Gobernarte Award for its AI initiatives for optimizing economic planning and managing climate risk. Overall, Ecuador offers a growing engineer base, a stable regulatory environment, competitive compensation, and lower local employer competition.

Uruguay

Uruguay punches well above its weight on AI maturity, ranking third in Latin America on CEPAL's 2025 Latin American AI Index with standout scores in infrastructure, human talent, and data availability. The country's 2025 Digital Agenda and National AI Strategy 2024–2030 reflect a long-standing government commitment to digital transformation, with AI pilot programs running across public sector institutions and active investment in upskilling the national workforce.

In 2025, Uruguay became the first Latin American country to sign the Council of Europe's legally binding Framework Convention on AI, covering human rights, democracy, and the rule of law. Uruguay also signed a US-Uruguay Memorandum of Understanding (MoU) on critical and emerging technologies in 2024, which is focused on fostering innovation and economic opportunities between the two nations. This creates favorable conditions for North American enterprises hiring AI engineers in Uruguay.

The compliance risks of cross-border hiring

Enterprise AI hiring teams often assume that engaging an AI engineer in LATAM as an independent contractor is a straightforward transaction involving a statement of work, a wire transfer, and a delivery milestone. That assumption is accurate only if the engagement is genuinely independent in the eyes of the local jurisdiction. In most LATAM countries, the criteria for true independent contractor status are more restrictive than many enterprises expect.

The specific risk in most ad-hoc arrangements is misclassification. If a LATAM AI engineer works exclusively or primarily for one enterprise client, receives direction from that client's managers, uses client-provided tools, and operates within a client-defined schedule, some LATAM labor regulators and courts may view that relationship as employment, regardless of what the contract says. Misclassification can trigger back-payment of social contributions, penalties, and in some cases, personal liability for the hiring manager who signed the agreement.

Additionally, many LATAM countries require that cross-border contractor payments comply with specific tax withholding and reporting frameworks. Contractors receiving foreign income must declare it to local tax authorities, and enterprises that pay LATAM contractors directly without structuring the arrangement correctly risk triggering social contribution obligations, permanent establishment exposure in the contractor's country, and potential criminal liability for simulating an independent contractor relationship.

IP ownership adds a third layer of complexity. In several LATAM countries, default IP rules under employment or contractor law do not automatically transfer ownership of work product to the hiring company. An enterprise that builds a proprietary AI model using LATAM contractors without well-drafted IP assignment clauses in the contractor agreement may find that ownership of that model is contested, a serious exposure for any business treating its AI assets as a competitive differentiator.

However, these risks are not reasons to avoid hiring in LATAM. They point instead to the importance of structuring engagements correctly from the start, and that is precisely where having the right compliance infrastructure matters.

Hire AI engineers in LATAM compliantly with Deel

AI engineers in LATAM present valuable opportunities, and the enterprises that move first will have hiring and cost advantages that compound over time. But the challenge many enterprises face is how to tap into global talent compliantly and at scale.

Deel Hire is the front door to modern hiring. It helps teams understand their hiring options and guides each role into the right employment model—whether EOR, PEO, direct employment under local entity, or contractors. By connecting recruiting, verification, contracts, onboarding, and HR setup into one workflow, Deel Hire removes handoffs and embeds compliance from day one. As workforce needs change, Deel Hire adapts without forcing teams to switch tools or redesign processes.