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Hire Generative AI Developers

Hire top-tier Generative AI developers from Latin America. Tecla connects U.S. companies with elite nearshore AI talent: engineers experienced in LLMs, NLP, model fine-tuning, prompt engineering, and more.

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Our Generative AI Services & Delivery Models

Staff Augmentation
Tap into our vetted Generative AI talent pool to integrate expert developers into your internal AI teams. Maintain full control while reducing hiring friction.
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AI Pods
Need a full AI team? We build agile Pods that can include ML Engineers, Data Scientists, Prompt Engineers, and Product Managers. These nearshore teams are led by an AI-savvy PM or Scrum Master and work in full collaboration with your in-house leadership.
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Smarter Hiring for Generative AI

Generative AI moves fast, your hiring strategy should, too

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With a nearshore approach, you can access specialized AI talent faster than traditional U.S. recruiting.

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Time zone alignment enables rapid iteration and model deployment.

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Reduce costs without compromising on talent quality.

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Flexible engagement models support both R&D and production-ready AI systems.

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Map of Latin America with location pins showing diverse people in Mexico, Costa Rica, Colombia, Peru, Brazil, Argentina, and Chile.

Case Studies

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2014
Maya Patel
PyTorch
TensorFlow
LLMs
MLOps

Maya Patel

US

Head of AI

From 
 
 
 Years of Experience
Maya has spent the last decade leading AI teams in the Bay Area, with experience scaling ML infrastructure at two AI-first startups, one acquired in 2022. Her work spans LLM fine-tuning, retrieval systems, and bringing AI features from research to production at scale. She's especially passionate about helping engineering teams cross the gap between AI experimentation and durable production systems, and mentors AI engineers throughout the San Francisco community.
2015
David Kim
PyTorch
Python
Spark
Kubernetes

David Kim

US

Senior ML Engineer

From 
 
 
 Years of Experience
David is a senior ML engineer with a decade of experience building production machine learning systems for fintech and enterprise SaaS companies in New York. He specializes in real-time recommendation engines, fraud detection models, and the data pipelines that power them. His recent work has focused on integrating LLM-based agents into existing ML stacks, and he contributes to several open-source ML infrastructure projects.
2017
Sarah Ortiz
Python
LangChain
OpenAI API
Pinecone

Sarah Ortiz

US

Senior LLM Engineer

From 
 
 
 Years of Experience
Sarah is an LLM engineer based in Austin with deep experience shipping agentic AI applications, RAG systems, and conversational AI products. She came to LLM engineering from a traditional NLP background and has built production AI features for companies in healthcare, legal tech, and developer tools. She's known for pragmatic architecture choices and getting AI products from prototype to scale quickly.
2017
Lucas Arneiro
Machine Learning
Python
C++

Lucas Arneiro

BR

AI Developer

From 
Brazil
 
 
 Years of Experience
Lucas is a Mechatronics Engineer with a post-graduate degree in Software Engineering. Later, he specialized in AI and Machine Learning, combining his expertise in providing agile AI solutions for several world-recognized companies like KPMG Lighthouse. He's an expert in different technologies such as Python, C++, SQL, Automation Anywhere, Machine Learning, Azure Microsoft, and Big Data.
2013
Cesar Juarez
Machine Learning
Deep Learning
Python

Cesar Juarez

MX

Machine Learning Engineer

From 
Mexico
 
 
 Years of Experience
César is an accomplished Machine Learning Engineer with data science, statistical analysis, and machine learning expertise. He excels in using Python and various frameworks, including TensorFlow and Scikit-learn. César has a proven track record of working with international companies and startups, collaborating in globally distributed teams. With strong English proficiency and experience in remote work, he seamlessly integrates into diverse environments. César's passion for open-source projects and commitment to continuous learning make him valuable in developing machine learning solutions.
2015
Natalina Neves
Machine Learning
Deep Learning
Python

Natalina Neves

AR

AI Developer

From 
Argentina
 
 
 Years of Experience
Natalina is a Software Engineer with several specializations in AI, Machine Learning, and Deep Learning. She co-founded a sales & customer success coaching software that helps contact center teams succeed by providing AI-powered guidance after every call. Her area of expertise is connecting AI and sales teams to drive results faster and more efficiently.
2008
Pedro Pereira
Machine Learning
Data Science
Python

Pedro Pereira

BR

ML / Big Data Engineer

From 
Brazil
 
 
 Years of Experience
Pedro is a seasoned professional with expertise in data engineering, advanced analytics, and machine learning. With over 15 years of experience, he has a proven track record in managing projects, implementing AI/ML strategies, and resolving complex problems. Pedro's skills include data science, machine learning, cognitive solutions, and a wide range of technical tools such as Python, Pyspark, SQL, Hadoop, and AWS.
2015
María Curetti
C++
SQL
Python

María Curetti

AR

AI Developer

From 
Argentina
 
 
 Years of Experience
María is an Electronic Engineer with a Ph.D. in Engineering Sciences. She is a seasoned AI developer and Data Scientist with experience in one of LatAm's biggest e-commerce platforms, Mercado Libre, and deep learning research in educational institutions. She is an expert in data classification and models, simulations, neural network design, and programming languages like C++, Python, SQL, and others.

10+ Years Making GenAI Hiring Processes Easier

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The Benefits of Hiring in Latin America

Top Talent

Top AI Talent

Tap into a pipeline of AI experts proficient in LLMs, multimodal architectures, embeddings, fine-tuning, and cloud-based ML workflows.

Cost Effective

Cost-Effective Innovation

Our nearshore teams offer competitive rates, making AI experimentation and scale more feasible.

Shared Timezone

Frictionless Collaboration

hared time zones and cultural fluency create a smoother feedback loop, especially critical when testing models in production.

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Rapid Scaling

From PoC to production: scale your AI capabilities in weeks, not months.

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In-Person Possibilities

Proximity allows occasional face-to-face collaboration, building trust and alignment.

Why Tecla?

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Elite Vetting for AI Developers

We don’t just look at resumes. We test technical skills in AI frameworks (TensorFlow, PyTorch, LangChain), assess English communication, and validate experience through projects and references.

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Built-In Compliance

From NDAs to IP protection, we ensure every AI project is legally safe and HR-compliant. Our regional footprint means we handle local contracts, benefits, and payroll.

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AI-Ready Infrastructure

Need cloud credits, high-memory compute, or GPU access? We help ensure your engineers have the right setup from day one.

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Success Management Layer

Your Tecla Success Manager ensures retention, performance reviews, and roadmap alignment. That’s peace of mind as you scale GenAI capabilities.

Frequently asked questions

What is a nearshore Generative AI team?

It's a dedicated team of AI professionals located in Latin America, working in sync with your product and data teams. They specialize in LLMs, prompt engineering, and full AI lifecycle delivery.

How much does it cost to hire generative AI developers?

Rates vary by skill level and team size, but expect significant savings compared to the U.S.-based hires. Tecla provides a transparent pricing model with flexible contracts.

Which AI roles can Tecla help with?

  • Machine Learning Engineers
  • Prompt Engineers
  • AI Product Managers
  • MLOps & DevOps Engineers
  • Data Scientists & Annotators
  • QA Engineers for AI systems

How fast can we start?

We typically place vetted candidates within 2–3 weeks. Full Pods can be assembled in under 30 days.

Have any questions?
Schedule a call to discuss in more detail.
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Hire Generative AI developers with the agility of nearshore. Start building your future AI stack today.

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