Build AI Products That Ship
You need AI engineers who build production systems—not researchers who write papers. Engineers who ship LLM-powered products, design RAG pipelines, and know the difference between a demo and a scalable system.
Get vetted AI/ML developers in 48 hours. 50-70% less than US rates.
AI/ML Roles We Place
AI Engineers
Build production AI applications with LLMs, RAG pipelines, and AI-native products. OpenAI, Anthropic Claude, LangChain, vector databases.
Best for: AI-powered products, chatbots, document analysis, content generation, workflow automation.
ML Engineers
Train, deploy, and scale machine learning models. Custom model development, MLOps, feature engineering, model serving infrastructure.
Best for: Custom ML models, recommendation systems, predictive analytics, computer vision, model optimization.
Data Engineers
Build data pipelines and infrastructure. ETL workflows, data warehouses, real-time streaming, analytics infrastructure.
Best for: Data pipelines, analytics platforms, data lakes, real-time processing, BI infrastructure.
NLP Engineers
Natural language processing specialists. Text classification, sentiment analysis, named entity recognition, language models.
Best for: Text analysis, search systems, chatbots, document processing, multilingual applications.
When to Hire Each Role
| Your Need | Hire This |
|---|---|
| Building with ChatGPT/Claude APIs | AI Engineer |
| RAG system for internal knowledge | AI Engineer |
| Custom model for your domain | ML Engineer |
| Recommendation engine | ML Engineer |
| Data pipeline infrastructure | Data Engineer |
| Analytics and reporting | Data Engineer |
| Text classification/extraction | NLP Engineer |
Not sure? Start with an AI Engineer—they can assess whether you need ML or data engineering support.
Common AI/ML Tech Stacks
LLM & AI Frameworks: OpenAI, Anthropic Claude, LangChain, LlamaIndex, Hugging Face, PyTorch, TensorFlow
Vector Databases: Pinecone, Weaviate, Qdrant, Chroma, pgvector
Data & ML Infrastructure: Python, FastAPI, AWS (Bedrock, SageMaker), GCP (Vertex AI), Spark, Airflow
Evaluation & Monitoring: LangSmith, Weights & Biases, MLflow
AI/ML Team Combinations
Solo AI Engineer For: Adding AI features to existing products, chatbots, RAG systems Typical: 1 AI Engineer working with your existing team
AI Product Pair For: AI-native products requiring frontend integration Typical: 1 AI Engineer + 1 Full-Stack Developer
Full AI Team For: Complex AI products or ML infrastructure Typical: 2 AI Engineers + 1 ML Engineer + 1 Data Engineer
Frequently Asked Questions
What’s the difference between AI Engineers and ML Engineers?
AI Engineers integrate existing AI models (OpenAI, Claude) into products—RAG systems, chatbots, AI features. They’re software engineers who specialize in AI.
ML Engineers train custom models from scratch—recommendation systems, predictive models, computer vision. They work closer to data science.
Most companies in 2026 need AI Engineers because pre-trained LLMs handle most use cases. Hire ML Engineers when off-the-shelf models don’t meet your needs.
How much do AI/ML developers cost?
AI Engineers and ML Engineers: $6,000-10,000/month (50-70% less than US rates of $15,000-20,000+/month). AI/ML roles command 20-40% premiums over standard developers due to specialized expertise.
Can I hire a complete AI product team?
Yes. We place individual AI engineers or complete teams: AI Engineers + ML Engineers + Data Engineers + Full-Stack Developers. Start with one and scale as needed.
Do you have developers experienced with RAG and LLMs?
Yes. Our AI engineers have production experience with RAG architectures, vector databases, LLM orchestration (LangChain, LlamaIndex), prompt engineering, and AI product deployment.
Ready to Build Your AI Team?
Get Started → — Meet vetted AI/ML developers in 48 hours.
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- Hire Nearshore Developers — Why Latin America
- Hire Developers for Startups — Startup hiring guide