Descripción del puesto

We're looking for an AI Engineer to build and ship production-grade generative AI solutions: intelligent assistants, RAG systems, and autonomous agents. 100% hands-on role with end-to-end ownership: architecture, deployment, monitoring, and continuous improvement. Not research, not POCs — making it work in production.

💼 What you'll do

• Build LLM applications and AI agents with LangChain / LangGraph or similar.
• Implement RAG pipelines: embeddings, vector databases, hybrid search.
• Integrate multiple LLMs (OpenAI, Anthropic, Gemini, open source) based on cost, latency, and quality.
• Deploy on cloud (AWS / GCP / Azure) and monitor performance, drift, and cost.
• Implement LLM evals to ensure response quality.

Requisitos

✅ What we're looking for

• 4+ years developing with Python.
• Real production experience with LLMs: prompt engineering, RAG, tool calling.
• Hands-on with vector databases (Pinecone, Chroma, pgvector).
• Cloud + solid engineering practices: testing, version control, CI/CD.
• Intermediate/advanced English.

⭐ Nice to have

• Agent frameworks (CrewAI, AutoGen) and protocols like MCP.
• Fine-tuning of open-source models, MLOps.
• Experience with US / European clients.