Roles we hire for
AI Engineer in Colombia
Access senior AI Engineer talent in Colombia’s top tech hubs—vetted by experience US leaders, not recruiters with checklists.
benefits
Why hire a AI Engineer from Colombia?
Colombia's AI engineering talent is growing rapidly, driven by demand from fintech and logistics companies where machine learning has moved from experiment to product. Fraud detection, credit scoring, and demand forecasting at companies like Bancolombia, Addi, and Rappi created practical ML engineers — people who know how to get a model into production and keep it working, not just how to train one in a controlled environment. Bogotá in particular has developed a strong data science and AI community, with university programs increasingly aligned to the applied AI and LLM engineering skills in demand from US product companies.
Common frameworks include: FastAPI, Hugging Face Transformers, Scikit-learn, LlamaIndex, RedisIBM, Xerox.
Notable companies from Colombia include: Rappi, Bancolombia, Addi, Frubana, Komet Sales.
Timezone:
(UTC-05:00) Colombia (COT)
English Proficiency:
Moderate
Tech Hub(s):
Bogotá, Medellín
screening
How Expand evaluates AI Engineer candidates
We look for AI engineers who have taken ML systems into production and understand what that transition actually requires — evaluation frameworks, monitoring, fallback behavior, and the infrastructure that keeps AI features reliable at scale. Every candidate goes through a structured recruiter screening, a custom take-home technical assessment, and a deep dive interview. The take-home evaluates LLM integration design, RAG system thinking, and how candidates approach model evaluation. The deep dive probes production ML architecture, how they have diagnosed AI system failures, and their approach to building AI features in collaboration with product teams.
Technical depth we assess:
LLM integration and production AI reliability
ML pipeline design and model serving
RAG system architecture and retrieval optimization
Model evaluation and output monitoring
Data-intensive AI patterns from fintech and logistics contexts
salary
Salary ranges for AI Engineers based in Colombia
Experience:
4–6 years
Monthly rate (USD):
$3,500 – $5,500
Description:
Mid-senior AI engineer, strong Python and applied ML fundamentals, capable of owning AI feature development and ML pipeline design
Experience:
7–10 years
Monthly rate (USD):
$6,000 – $8,500
Description:
Senior AI engineer, experienced in production ML systems, capable of leading AI architecture decisions and model evaluation design
Experience:
10+ years
Monthly rate (USD):
$10,000 – $13,000
Description:
Staff or architect level, deep applied AI expertise, capable of driving technical direction for an AI engineering function
process
How Expand works
1. You tell us what you need
We align on role requirements, team context, and success criteria in a focused intake call. Your long-term goals matter to us.
2. We source and screen
We do the searching and every shortlisted candidate meets with an experienced leader to make sure they clear the bar.
3. You interview 2-3 finalists
candidates who are already qualified and aligned. The focus is on decision-making, not filtering or second-guessing.
4. They start as your contractor
We handle logistics, support onboarding through the first 90 days, and invest directly in retention.
get answers
Frequently asked questions
What's the typical English level of roles in this country?
English proficiency varies by seniority and market. Senior engineers across our Latin American markets typically have strong written English and are comfortable in async communication, code reviews, and technical documentation. Spoken fluency ranges from conversational to highly proficient at the senior level — Uruguay and Argentina trend strongest overall. We assess communication quality directly as part of our screening process, so every candidate we present has already demonstrated the level needed to work effectively on a US distributed team.
Can engineers based in this country work US hours?
Yes. Latin American tech hubs operate between UTC-3 and UTC-6, which provides four to seven hours of synchronous overlap with US East Coast teams and full overlap with US Central and Mountain time. Most senior engineers in our markets have been working with US teams for years and are accustomed to aligning their schedules accordingly. We confirm availability and working hour expectations during the screening process before any candidate is presented.
How do salary expectations compare to US-based engineers in this role?
Senior engineers placed through Expand typically work on a contractor basis at monthly rates ranging from $3,500 to $10,000 depending on seniority, role, and market — compared to $15,000 to $25,000 or more per month for equivalent full-time US-based hires when total compensation is factored in. The savings are significant without the trade-off in quality that lower-cost offshore markets often involve. All rate ranges for specific roles and countries are detailed on each individual hire page.
What kind of companies do you consult for?
Absolutely. In fact, many of our most successful projects are built on close collaboration with internal R&D, data science, or innovation units. We integrate seamlessly, offering fresh perspectives while respecting existing knowledge and workflows. Our role is to complement, not replace.
Can you work with in-house R&D teams?
Absolutely. In fact, many of our most successful projects are built on close collaboration with internal R&D, data science, or innovation units. We integrate seamlessly, offering fresh perspectives while respecting existing knowledge and workflows. Our role is to complement, not replace.
Are your solutions off-the-shelf or built from scratch?
Absolutely. In fact, many of our most successful projects are built on close collaboration with internal R&D, data science, or innovation units. We integrate seamlessly, offering fresh perspectives while respecting existing knowledge and workflows. Our role is to complement, not replace.
How does the consultancy process start?
Absolutely. In fact, many of our most successful projects are built on close collaboration with internal R&D, data science, or innovation units. We integrate seamlessly, offering fresh perspectives while respecting existing knowledge and workflows. Our role is to complement, not replace.
Do you specialize in any particular areas?
Absolutely. In fact, many of our most successful projects are built on close collaboration with internal R&D, data science, or innovation units. We integrate seamlessly, offering fresh perspectives while respecting existing knowledge and workflows. Our role is to complement, not replace.
What kind of companies do you consult for?
Absolutely. In fact, many of our most successful projects are built on close collaboration with internal R&D, data science, or innovation units. We integrate seamlessly, offering fresh perspectives while respecting existing knowledge and workflows. Our role is to complement, not replace.
Can you work with in-house R&D teams?
Absolutely. In fact, many of our most successful projects are built on close collaboration with internal R&D, data science, or innovation units. We integrate seamlessly, offering fresh perspectives while respecting existing knowledge and workflows. Our role is to complement, not replace.
Are your solutions off-the-shelf or built from scratch?
Absolutely. In fact, many of our most successful projects are built on close collaboration with internal R&D, data science, or innovation units. We integrate seamlessly, offering fresh perspectives while respecting existing knowledge and workflows. Our role is to complement, not replace.
How does the consultancy process start?
Absolutely. In fact, many of our most successful projects are built on close collaboration with internal R&D, data science, or innovation units. We integrate seamlessly, offering fresh perspectives while respecting existing knowledge and workflows. Our role is to complement, not replace.