Descripción de la oferta
AI Engineer / LLM Engineer Siga leyendo para descubrir lo que necesitará para tener éxito en este puesto, incluyendo habilidades, cualificaciones y experiencia. About the roleWe are looking for an AI Engineer to join a dynamic AI team within an international technology environment.In this role, you will design, build, and deploy LLM-powered applications, RAG pipelines, multi-agent systems, and scalable AI solutions on AWS.You will work at the intersection of software engineering, AI engineering, data pipelines, and cloud deployment, contributing to real use cases across the airline group. This role is highly hands-on and focused on building intelligent systems that move from experimentation to production.You will collaborate closely with domain experts, Data Engineers, Product Managers, and a Tech Lead to translate business needs into reliable and scalable AI products.If you enjoy working with LLMs, agents, RAG, vector databases, Python APIs, and AWS-native AI services, this could be a great fit. What you’ll do Design, build, and maintain LLM-powered applications and multi-agent systems using frameworks such as LangChain, LangGraph, CrewAI, or similar Develop and optimise RAG pipelines, including document ingestion, chunking strategies, embedding generation, retrieval logic, and vector search Implement and manage vector databases such as pgvector on Aurora, OpenSearch, Pinecone, or similar Build and maintain data and ETL pipelines using Apache Airflow, Prefect, or similar tools Develop backend services and APIs in Python / FastAPI to serve AI models, RAG systems, and agent workflows Deploy and manage AI workloads on AWS services such as Bedrock, SageMaker, Lambda, S3, Aurora/RDS, EC2 Work with Docker and Kubernetes to containerise and orchestrate AI workloads Design and execute evaluation frameworks for LLM outputs, including automated testing, LLM-as-judge approaches, and human-in-the-loop review Work with LLM APIs and orchestration tools such as AWS Bedrock, OpenAI API, Anthropic API, or similar Apply prompt engineering, fine-tuning techniques, and LLM evaluation methodologies Collaborate with domain experts, Data Engineers, Product Managers, and the Tech Lead to turn business requirements into AI solutions Participate in Scrum ceremonies and contribute to a collaborative Agile engineering culture Stay up to date with the rapidly evolving AI/ML ecosystem and proactively propose new tools, improvements, and approaches Mentor junior team members and share AI engineering best practices Must Have 3–5 years of experience in Software Engineering, with at least 1–2 years focused on AI / ML Engineering Strong proficiency in Python Experience with AI/ML and LLM frameworks such as LangChain, LangGraph, Hugging Face, PyTorch, or similar Hands-on experience building RAG systems, including embeddings, vector stores, semantic search, and hybrid search strategies Experience working with LLM APIs such as AWS Bedrock, OpenAI API, Anthropic API, or similar Solid understanding of prompt engineering, fine-tuning techniques, and LLM evaluation methodologies Hands-on experience with AWS services such as EC2, S3, Lambda, Aurora/RDS, Bedrock, SageMaker Experience with Docker and Kubernetes Familiarity with data pipeline tools such as Apache Airflow, Prefect, or similar Experience developing backend services or APIs, ideally with FastAPI Proficiency with Git and software engineering best practices Experience working in a Scrum Agile environment Strong problem-solving, analytical thinking, communication, and teamwork skills Fluent English Nice to Have Experience with multi-agent architectures and protocols such as A2A or MCP Familiarity with MLOps practices: model versioning, experiment tracking, MLflow, Weights & Biases, and CI/CD for ML Experience with observability and evaluation platforms for LLMs such as Langfuse, Datadog LLM Observability, LangSmith Knowledge of graph databases or knowledge graphs for enhanced retrieval Experience with CI/CD pipelines using tools such as GitHub Actions Familiarity with Infrastructure as Code, especially Terraform Experience with code quality and security tools such as SonarCloud, Snyk Experience in aviation, travel, or large-scale digital environments Spanish language skills are a plus Hybrid model - 2 days onsite per week Why join this project? People first – diverse and inclusive culture in an international environment. Build production-ready LLM applications, RAG systems, and agentic AI solutions Work with cutting-edge AI technologies across the LLM, agents, vector search, and AWS ecosystem Contribute to scalable engineering practices around AI applications, data pipelines, evaluation, and deployment Gain hands-on exposure to AWS-native AI services such as Bedrock, SageMaker, Lambda, S3, and Aurora Be part of a fast-moving AI environment where experimentation, ownership, and impact are highly valued High team stability and collaborative culture. €1200 per year training budget and continuous learning opportunities. Flexible compensation model. Private health insurance and benefits package. Flexible working hours and hybrid model. Wellhub: fitness, wellness, and mental health support. Football and paddle tennis teams sponsored by Capitole. Team buildings, global events, and strong tech communities. Want to know more about us? Click here and discover all the details. Curious about our culture? Check out what people are saying about us on Glassdoor. We know that not every candidate will meet 100% of the requirements. If your profile doesn’t match perfectly but you believe you can add value, we’d still love to hear from you. Ready for the challenge? Apply now and help build intelligent, scalable, production-ready AI solutions.Empowering People, Unlocking Innovation.Information Security NoticeThe employee will have access to confidential information related to Capitole and the assigned project. xcskxlj Compliance with internal security and information protection policies is mandatory.
