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As AI continues to reshape every industry—from healthcare to finance to consumer apps—the need to hire AI developers with the right skillset is more urgent than ever. Companies looking to remain competitive must invest in engineering teams that can build, integrate, and scale AI-powered solutions.
This guide breaks down everything you need to know to hire top AI developers in 2025—from must-have skills to modern tech stacks, hiring strategies, interview tips, and salary benchmarks across the U.S. and Latin America.
Hiring developers in Latin America can reduce salary costs by 40–60% compared to U.S.-based hires. Despite the lower costs, the quality of engineering talent remains high, especially in AI-related roles.
Most Latin American countries operate within U.S. business hours, making real-time collaboration smooth and effective. Teams can easily schedule standups, code reviews, and sprint planning without delays.
→ Why time zone alignment matters
Top universities and coding bootcamps in countries like Brazil, Mexico, and Argentina now offer AI and ML-focused programs. The region is producing developers skilled in tools like TensorFlow, PyTorch, and OpenAI APIs.
→ Top countries in Latin America for tech talent
Latin American developers are fluent in English and experienced working with U.S. teams. They’re well-versed in agile practices, async communication, and tools like GitHub, Slack, and Jira.
→ How Latin American developers work with U.S. companies
Hiring AI developers in 2025 means filtering for a unique mix of traditional software engineering capabilities and modern AI-specific expertise. As AI becomes more deeply integrated into digital products—from chatbots and recommendation engines to predictive analytics and generative AI tools—your developers must be fluent in the evolving AI landscape.
Here are the essential skills to prioritize:
Programming Languages & Frameworks: Fluency in Python, the dominant language for machine learning, is non-negotiable. Developers should also be proficient in TensorFlow, PyTorch, and scikit-learn for building, training, and deploying ML models.
Data Engineering & ETL: AI developers should know how to build robust data pipelines using tools like Apache Airflow and Spark, and be experienced in model deployment, especially in cloud environments.
→ What is ETL and why is it essential for AI development?
LLMs & Prompt Engineering: As LLMs (Large Language Models) become foundational, your hires should understand prompt engineering, fine-tuning, and how to safely and efficiently work with models like GPT-4, Claude, or Gemini.
→ What is prompt engineering? (OpenAI)
Tooling & APIs: Look for experience with AI tools like LangChain, Hugging Face Transformers, and OpenAI APIs—especially if your product includes chat interfaces or generative components.
→ Hugging Face Transformers Documentation
Cloud AI Services: Ideal candidates should be comfortable with cloud platforms like AWS SageMaker, Google Vertex AI, and Azure ML, which are standard for deploying scalable AI solutions.
→ Deploying Python ML models on AWS
To hire AI developers capable of building production-grade systems, make sure they are familiar with this full-stack toolbox:
Languages & Frameworks
ML Ops Tools
Cloud & DevOps
Data Tools
To avoid wasting time or hiring the wrong fit, follow these proven steps:
Not all AI developers are the same. Some specialize in building models, others in data engineering or product integration. Determine whether you need a machine learning engineer, a data pipeline expert, or someone skilled in LLM integrations and fine-tuning.
Finding great talent among hundreds of applicants is time-consuming. Partnering with platforms like Revelo gives you access to pre-vetted AI developers in Latin America—engineers with verified experience in real-world AI projects.
Instead of generic coding tests, use practical assessments:
These exercises will surface engineers who can hit the ground running.
Since most teams are hybrid or remote, communication skills are just as important as technical ability. Look for candidates experienced in asynchronous workflows, collaborative tools like GitHub and Slack, and who are fluent in English.
AI job postings grew 38% from 2020 to 2024 (LinkedIn)
Over 30% of dev job listings now include AI or ML-related skills
76% of developers now use AI tools like GitHub Copilot or ChatGPT
A Revelo não é um banco, mas nosso sistema de transferência de pagamentos funciona por meio de contratos entre empresas e contratantes. Graças às nossas parcerias com terceiros, conseguimos oferecer taxas de transferência muito abaixo do mercado. Além disso, nosso modelo de negócios diversificado nos dá uma vantagem competitiva única. Aproveite essa oportunidade para economizar e receba seus pagamentos de forma eficiente com a Revelo!
Use coding challenges, real-world tasks, and portfolio reviews. Focus on practical skills with tools like Python, TensorFlow, or OpenAI APIs—not just academic knowledge.
It enables real-time communication, quicker standups, and faster iteration—especially important when shipping AI features on tight timelines.
Developers in Latin America offer high-quality engineering skills, strong English fluency, cultural compatibility with U.S. teams, and overlapping time zones.
Yes. Many have hands-on experience with LLMs, machine learning frameworks, and APIs like Hugging Face and OpenAI—especially those vetted through Revelo.
Look for adaptability, collaboration, and AI tooling experience. Developers who know how to use GitHub Copilot, deploy ML models, and integrate APIs will thrive on modern teams.
In 2025, hiring developers—especially those skilled in AI—is less about supply and more about finding the right fit. Latin America offers a unique opportunity: world-class talent at competitive rates, operating in your time zone, and fluent in the tools that power modern AI systems.
Whether you're scaling an ML platform or integrating generative AI into your product, the right team makes all the difference.
Explore pre-vetted AI developers at Revelo.
