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# AI Engineer - AI-Driven Software Development

- **Company:** E-frontiers
- **Location:** Madrid, Spain (Remote available)
- **Salary:** €65,000.0
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Java (Programming Language), JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Code Generation, Code Review, Computer Programming, Continuous Integration, Programming Tools, Graph Database, Python (Programming Language), Systems Development Life Cycle, Software Engineering, Systems Integration, Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, Backend, Agentic-AI, Kotlin, Build Management, Kubernetes, Terraform, Docker
- **Published:** October 1, 2026
- **Apply:** https://www.adzuna.es/details/5904513971

## About the Role

* 5+ years of software engineering experience , ideally in backend or full-stack environments.
 * Strong programming experience with Java, Python, JavaScript, or Kotlin .
 * Hands-on experience integrating LLMs into software engineering or product workflows .
 * Good understanding of RAG, embeddings, vector databases, and LLM orchestration .
 * Experience with MCP, context engineering, or agentic workflows .
 * Solid understanding of software development practices, APIs, CI/CD, and production systems.
 * Experience with Docker, Kubernetes, and/or Terraform .
 * Strong problem-solving skills and the ability to turn ambiguous ideas into practical, scalable solutions.
 * A genuine interest in how AI can improve the way software engineers work.

Nice to Have

 * Experience with LangChain, LangGraph, or similar frameworks.
 * Experience with intelligent testing or AI-assisted code review.
 * Knowledge of graph databases or knowledge graphs.
 * Experience with platform engineering or Infrastructure as Code.
 * NLP or applied AI experience.
 * Experience building internal developer tools.

## Description

* Design and build AI-powered SDLC solutions, including code generation, automated code reviews, intelligent testing, and documentation.
 * Develop MCP-based tools and extensions that give AI systems access to relevant engineering context and tools.
 * Apply context engineering techniques to improve the accuracy, reliability, and relevance of LLM-powered workflows.
 * Build LLM-integrated workflows across CI/CD pipelines.
 * Work with LLM orchestration, prompt engineering, structured outputs, and tool calling.
 * Develop and integrate RAG-based solutions using embeddings and vector databases.
 * Implement evaluation, observability, monitoring, and guardrails for AI systems.
 * Work closely with engineering and product teams to identify new opportunities for AI-driven automation and productivity.


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