AI Engineer

This is a fully remote position, open to applicants in Spain.

📋 Description

• Act as a technical reference in the development of Generative AI solutions

• Design and develop solutions based on LLMs and foundational models

• Implement advanced RAG pipelines, GraphRAG architectures, and hybrid retrieval systems

• Create autonomous agents and solutions based on multi-agent architectures

• Orchestrate complex workflows using LangChain and LangGraph

• Manage the context, state, and memory of agents

• Integrate AI solutions with APIs, services, and corporate data sources through Tool Calling

• Design, deploy, and maintain servers based on Model Context Protocol (MCP)

• Process, transform, and ingest unstructured data from documentary sources

• Implement validations, controls, and guardrails to reduce hallucinations and protect sensitive data

• Design evaluation mechanisms, observability, and traceability for LLM models and applications

• Package, deploy, and put into production Generative AI solutions while applying best practices in LLMOps

• Develop unit and integration tests

• Participate in continuous integration and deployment processes

⛳️ Requirements

• At least 3 years of experience in Generative Artificial Intelligence projects

• Strong knowledge of software engineering, Clean Code principles, and architectural design

• Proven experience designing architectures for GenAI solutions, selecting agents, foundational models, vector databases, and orchestration tools

• Proficiency in Python and experience with TypeScript

• Experience working with vector databases and optimizing semantic, hybrid, and similarity searches

• Advanced knowledge of LangChain, LangGraph, or LangFlow

• Experience in building and orchestrating autonomous agents and multi-agent systems

• Practical experience in corporate integration through APIs, Tool Calling, and MCP servers

• Understanding of advanced RAG techniques, automated document ingestion, and knowledge graph-based architectures like GraphRAG

• Experience in preprocessing complex unstructured data

• Knowledge of security mechanisms, validation, and hallucination prevention

• Experience applying LLMOps practices: observability, evaluation, traceability, and monitoring of LLM-based solutions

• Familiarity with Langfuse, LangSmith, or similar tools

• Experience working with Git, Docker, and CI/CD pipelines

• Experience creating unit tests, integration tests, and continuous deployment processes

🏝️ Benefits

• Remote or hybrid work model

• Buddy system for support from day one

• Annual training plan

• Official certifications

• Learning spaces

• 100% subsidized medical insurance

• Flexible compensation through Edenred

• 25 days of annual vacation

• Benefits focused on well-being

• Supportive and collaborative work environment

• Equal pay and opportunity