AI engineering · Machine learning · Data
Hire AI engineers and outsource machine learning to a nearshore team
Add AI, ML and data engineers to your team, or hand us a machine learning or AI agents initiative end to end. Same time zone, fluent English, production discipline.
AI roles you can hire
AI / LLM engineers
Retrieval-augmented generation, LLM integration, evaluation and guardrails.
Machine learning engineers
Model development, feature pipelines, deployment and monitoring (MLOps).
Data engineers
Pipelines, lakehouses and data quality that make AI possible.
Data scientists
Experimentation, forecasting and analytics tied to business decisions.
MLOps and cloud engineers
Infrastructure for training and serving models on Azure or AWS.
AI product engineers
Full-stack engineers who ship AI features into real products.
Why hiring AI engineers is hard, and how we make it easier
Demand for AI developers has grown much faster than the supply of engineers who have actually taken models to production. Many candidates can build a demo with an LLM API; far fewer can design retrieval pipelines, evaluate model quality, control cost and latency, and keep a system reliable once real users depend on it.
When you hire AI engineers through GIGA IT, candidates are evaluated by engineers who build these systems. We look for production experience: data preparation, evaluation methods, deployment, monitoring and retraining. You interview the shortlist and decide who joins.
AI roles in detail
- AI / LLM engineers design LLM applications, retrieval pipelines, prompt and evaluation strategies, and guardrails.
- Machine learning engineers build, train and evaluate models and take them to production.
- Data engineers build the pipelines and data platforms that models depend on.
- Data scientists frame problems, explore data and validate whether a model creates value.
- MLOps and cloud engineers automate deployment, monitoring, retraining and cost control.
- AI product engineers integrate AI features into existing products, from backend to user interface.
What our AI and machine learning engineers build
- LLM applications and RAG: assistants grounded in your documents and data, with evaluation and guardrails. See generative AI platforms.
- AI agents that automate document processing, support, reporting and back-office workflows, connected to your systems.
- Predictive models for forecasting, anomaly detection, quality and maintenance. See advanced analytics.
- Data and MLOps foundations: pipelines, feature stores, model registries, monitoring and CI/CD for models.
- AI features inside existing products, built by AI product engineers who work alongside your product team.
Ways to engage AI talent
Hire a single machine learning engineer to strengthen your team, add an AI pod with a tech lead, or outsource a defined machine learning project with clear success criteria. In every case you keep ownership of code, models and data under your agreement.
If you are still defining where AI fits, start with AI strategy consulting to prioritize use cases before you staff them. GIGA IT has delivered software since 2008, with 300+ specialists and 97% client retention.
Whichever model you choose, the engineers work inside your repositories, tools and ceremonies, and GIGA IT follows delivery and engagement so the team stays productive as priorities change.
How our AI engineers work
Production AI needs discipline. Our engineers define evaluation sets before building, measure quality, latency and cost on every change, version data, prompts and models, and monitor behavior after release. They design human review into workflows where errors are costly and document decisions so your team can maintain the system. Security and data access follow your policies, and models and data stay in the environments you approve.
Machine learning outsourcing, without losing control
Outsourcing machine learning works when the partner owns engineering quality and you keep ownership of data, models and decisions. We work inside your cloud and repositories, with documented models and handover by design.
- Use-case framing and data assessment
- Model development and evaluation
- Deployment, monitoring and retraining
- Knowledge transfer to your team
AI agents development
GIGA IT designs and builds AI agents that automate real workflows: document processing, support, reporting and internal operations, connected to your systems and governed by your security rules.
Why hire AI engineers from Latin America
Same or overlapping time zone
Engineers in Mexico, Colombia and Argentina work during U.S. business hours, so stand-ups, code reviews and incidents happen in real time.
Fluent English and cultural affinity
Teams used to U.S. rituals (sprints, PR reviews, demos, on-call) and comfortable talking directly with product owners.
AI built into the workflow
Engineers ship with AI copilots, automated testing and agents for repetitive work, under the same governance as your team.
Talk to an AI engineering lead
Let's talkFrequently asked questions
Can I hire a single AI engineer?
Yes. You can add one specialist or a full team, and scale as your roadmap changes.
What does machine learning outsourcing include?
From use-case framing and data preparation to model deployment and monitoring, with documentation and knowledge transfer.
Do you build AI agents?
Yes. We build AI agents integrated with enterprise systems and with human review where it matters.
Who owns the code and models?
You do. We work in your environments under your IP terms.
How do you vet AI engineers?
Engineers who build AI systems evaluate candidates on production experience: data, evaluation, deployment, monitoring and cost control.
Can AI engineers work with our existing data team?
Yes. They join your tools and rituals and work alongside your data and product teams.
Can you hire AI developers for a short project?
Yes. You can add engineers for a defined project or outsource a scoped machine learning project with clear success criteria.
Where do models and data run?
In the environments you approve, following your security and data-access policies.
Do you build AI agents?
Yes. Our engineers design and build AI agents connected to your systems, with permissions, logging and human review.
Can AI engineers join for a proof of concept and then scale?
Yes. Many teams start with one or two engineers on a scoped use case and add capacity once value is proven.