How to Hire a Nearshore AI Engineer from Latin America (and Why It’s a Smart Move)

You’ll save 30–70% on salary costs

The math is straightforward. AI engineers in the US typically command salaries between $88,000 and $176,000 annually, depending on experience level and specialization. By contrast, equally qualified AI engineers in Latin America generally earn between $42,000 and $96,000.

This isn’t about finding the cheapest possible labor. It’s about the reality of different markets and living costs. Latin American professionals earn competitive local salaries that provide an excellent standard of living, while still costing significantly less than their US counterparts.

What does this mean for your business? The budget that would normally cover one US-based senior AI engineer might allow you to hire two experienced nearshore engineers instead. This opens up possibilities for parallelizing development, pursuing more ambitious AI projects, or simply extending your runway.

Your team will work during your hours

One of the biggest challenges with traditional offshore hiring in places like India or the Philippines is the time zone difference. When your team is just starting their day, your offshore engineers are ending theirs. This creates a constant cycle of delayed responses and missed opportunities for real-time collaboration.

Hiring in Latin America eliminates this problem. Most LatAm countries align closely with US time zones. For example:

• Mexico shares time zones with the US Central and Pacific regions
• Colombia and Peru match US Eastern Time
• Argentina and Brazil are just 1–2 hours ahead of Eastern Time

This alignment means your nearshore AI engineers are available when you need them. When an ML model needs troubleshooting, your LatAm engineer can jump on a call immediately—not 12 hours later.

This time zone compatibility is particularly valuable for AI development, where iterative feedback and collaborative problem-solving are essential. Real-time communication enables faster development cycles and more efficient knowledge sharing.

Communication won’t be a barrier

LatAm professionals typically have strong English skills, particularly in the tech sector. Many have studied at US universities or worked with US companies previously. This English proficiency, combined with cultural similarities to the US, makes collaboration smooth and minimizes misunderstandings.

Beyond language, there’s significant cultural alignment. Latin American business culture shares many values with US workplaces—direct communication, results-oriented workflows, and, of course, similar working hours. This compatibility reduces friction and helps your nearshore team integrate seamlessly with your existing operations.

You’ll tap into specialized expertise that’s scarce in the US

Latin American countries have been investing heavily in AI education and research. Major universities in Mexico, Brazil, and Argentina offer specialized programs in artificial intelligence, machine learning, and data science.

These programs are producing graduates with expertise in:

• Machine learning algorithms and frameworks (TensorFlow, PyTorch)
• Natural language processing
• Computer vision and image recognition
• Reinforcement learning
• Deep learning
• Data preprocessing and feature engineering

The region’s growing tech ecosystem also means many professionals have practical experience implementing AI solutions for real-world business problems.

By expanding your search to Latin America, you significantly increase your chances of finding AI engineers with the specific skills you need.

1. Mexico

Mexico has emerged as a leading hub for AI development, with significant investment in both education and industry partnerships. The country’s AI sector has seen rapid growth, attracting over $640 million in investment in recent years, with machine learning making up 23% of the market.

Mexico’s advantages include:

• Time zone alignment with the US
• Strong technical universities like the Monterrey Institute of Technology
• Growing AI startup ecosystem in Mexico City and Guadalajara
• Excellent English proficiency, especially among tech professionals

For US companies, Mexico offers perhaps the simplest nearshore option due to its proximity and strong economic ties to the US.

2. Argentina

Argentina has long been recognized for its strong education system and technical talent. The country is home to prestigious universities with robust AI research programs, including the University of Buenos Aires (UBA) and the Buenos Aires Institute of Technology (ITBA).

Argentina’s advantages for AI hiring include:

• Well-established outsourcing industry with experience working with US companies
• Growing AI research community
• High English proficiency
• Only 1–2 hours ahead of US Eastern Time (depending on the time of year)

Argentina’s often turbulent economic situation also means that highly skilled professionals often seek opportunities with US companies, creating a win-win scenario for both sides.

3. Brazil

Brazil hosts Latin America’s largest AI talent pool, with major tech hubs in São Paulo, Rio de Janeiro, and Belo Horizonte. The University of São Paulo is ranked #1 in Latin America for machine learning and 85th globally.

Brazil’s advantages include:

• Extensive AI research community and academic programs
• Large-scale AI implementations across various industries
• Strong government support for AI development
• Growing ecosystem of AI startups and innovation centers
• Only 1–2 hours ahead of US Eastern Time

While English proficiency can vary more in Brazil than in some other LatAm countries, AI professionals typically have strong language skills, particularly those who have worked with international companies.

4. Colombia

Colombia’s tech industry has been rapidly expanding, with Medellín emerging as a major AI and data science hub. 

Colombia’s advantages include:

• Time zone alignment with US Eastern Time or Central (depending on the time of year)
• Strong English proficiency among tech professionals
• Growing investment in AI research and development
• Government initiatives supporting the tech sector
• Cultural compatibility with US business practices

Colombian AI engineers often have experience working with US companies, making for smooth integration with your existing teams.

5. Costa Rica

Though smaller than other countries on this list, Costa Rica has built a reputation for high-quality tech talent. The country is actively investing in AI development, with the government launching the National Artificial Intelligence Strategy (ENIA) 2024-2027.

Costa Rica’s advantages include:

• Excellent English proficiency (among the highest in Latin America)
• Political and economic stability
• Strong emphasis on education and skill development
• Growing ecosystem of tech companies and startups
• Same time zone as US Central Time

Costa Rica’s focus on sustainable development and ethical AI aligns well with companies looking to implement responsible AI practices.

Recruitment and staffing agencies: The hassle-free option

Working with a specialized nearshore AI recruitment agency is the most straightforward path for most companies. These partners have established networks of pre-vetted AI talent and understand the nuances of hiring in LatAm markets.

Good recruitment partners offer several advantages:

• They’ve already screened candidates for technical skills and English proficiency
• They understand local salary expectations and can help you make competitive offers
• They handle compliance with local labor laws and international payment logistics
• They provide ongoing support for both employers and placed candidates

While this approach typically involves recruitment fees (either upfront or as a percentage of the first year’s salary), the time saved and reduced risk of a bad hire justify the investment for many companies. You can focus on interviewing pre-qualified candidates rather than spending months figuring out how to navigate unfamiliar talent markets.

Freelance platforms: Ideal for project-based work

Platforms like Toptal, Upwork, and Arc.dev connect you with freelance AI engineers, which can be particularly useful for short-term projects or when testing a working relationship before making a longer-term commitment.

The advantages include:

• Direct access to a large pool of candidates
• Flexibility to scale resources up or down as needed
• Simplified payment processes through the platform

However, you’ll need to handle more of the vetting process yourself. If you go this route, prepare to:

• Develop a thorough technical assessment process
• Carefully review portfolios and past work
• Check references from previous clients
• Create clear project specifications and milestones

This approach works best when you have specific, well-defined projects and someone on your team with enough AI expertise to evaluate candidates effectively.

Job boards and direct hiring: The DIY approach

Posting on regional job boards can be effective if you have the time and resources for a hands-on hiring process. Sites worth considering include:

• Get On Board (focused on Latin American tech talent)
• LinkedIn (using location filters for LatAm countries)
• Stack Overflow Jobs (popular among developers throughout the region)

The advantages of this approach include:

• No agency fees
• Direct relationship with candidates from the start
• Complete control over the selection process

The downsides? You’ll need to invest significantly more time in screening candidates, and you’ll need to navigate the complexities of international hiring, contracts, and payments on your own.

This approach makes sense if you’re building a long-term hiring capability in Latin America or already have team members who understand these markets.

Referrals: The trusted connection

Never underestimate the power of your network. If you already work with Latin American talent, ask them for recommendations. If not, check with other founders or colleagues who have hired from LatAm before.

Personal recommendations often lead to the highest-quality candidates, as they come pre-vetted by people you trust. Plus, candidates are more likely to be a good cultural fit if they’re referred by someone who already understands your company.

Evaluate both technical and soft skills

The technical capabilities of AI engineers are obviously critical. Focus on candidates with proven experience in:

• Machine learning frameworks (TensorFlow, PyTorch, scikit-learn)
• Programming languages common in AI (Python, R, Julia)
• Data preprocessing and feature engineering
• Model deployment and MLOps
• Cloud platforms for AI development (AWS SageMaker, Azure ML, Google AI)

But soft skills are equally important for remote collaboration. The best nearshore AI engineers also demonstrate:

• Clear communication (both written and verbal)
• Problem-solving abilities and critical thinking
• Self-management and time discipline
• Adaptability to new tools and changing requirements
• Ability to explain complex technical concepts to non-technical stakeholders

During interviews, ask candidates to walk you through past AI projects, focusing on both technical implementation and how they collaborated with teammates and stakeholders.

Pay competitively for the local market

While you’ll save substantially compared to US salaries, don’t make the mistake of lowballing candidates. Research typical AI engineer salaries in your target countries and be prepared to pay at the higher end of those ranges to attract and retain top talent.

Remember, you’re not just competing with other US companies—you’re also competing with local tech firms and regional offices of global companies like Google and Microsoft. The best talent always has options.

Smart companies find the sweet spot—paying competitive rates for Latin America while still realizing significant cost savings compared to US salaries. This approach helps you build a stable, committed team that sticks with you for the long term.

Understand that LatAm resumes look different

When reviewing resumes from Latin American candidates, you’ll notice some differences from US-style resumes:

• They tend to be longer and more detailed (3–5 pages isn’t uncommon)
• They might include personal information like age, marital status, or photos
• Educational credentials may be presented differently
• Career trajectories might follow different patterns than what you’re used to seeing

Don’t let these differences distract you. Focus on the substance: the candidate’s skills, experience, and achievements. If you’re working with a recruitment partner, they can help interpret these differences accurately.

Ask the right interview questions

Effective interviews help you assess both technical capabilities and cultural fit. Good questions for nearshore AI engineer candidates include:

• “Walk me through an AI project you’ve implemented from concept to deployment. What challenges did you face, and how did you overcome them?”
• “How do you approach the ethical considerations of AI development?”
• “How do you stay current with the rapidly evolving field of artificial intelligence?”
• “Tell me about a time when you had to explain a complex AI concept to non-technical stakeholders.”
• “What approaches have you found most effective when collaborating with remote team members?”

These questions help you gauge not only technical expertise but also problem-solving approaches, ethical awareness, and communication skills.

Set clear expectations about work arrangements

Be explicit about your expectations regarding:

• Working hours and availability for meetings
• Communication protocols (which channels to use for what purposes)
• Reporting structures and feedback mechanisms
• Project management methodologies
• Time tracking and productivity measurement (if applicable)

Clear expectations from the start prevent misunderstandings and help your nearshore AI engineers integrate smoothly with your existing team.