AI Engineer / LLM EngineerObtenga más información sobre este puesto leyendo los detalles a continuación y luego envíe su solicitud para ser considerado.About the roleWe are looking for anAI Engineerto join a dynamic AI team within an international technology environment.In this role, you will design, build, and deployLLM-powered applications, RAG pipelines, multi-agent systems, and scalable AI solutionson AWS.You will work at the intersection ofsoftware engineering, AI engineering, data pipelines, and cloud deployment , contributing to real use cases across the group. This role is highly hands-on and focused on building intelligent systems that move from experimentation to production.You will work closely with Data Scientists, Platform and DevOps Engineers, Data Engineers, domain experts, Product Managers, and the Tech Lead to move AI solutions from experimentation into production.If you enjoy working withLLMs, agents, RAG, vector databases, Python APIs, and AWS-native AI services , this could be a great fit.What you’ll doDesign, build, and maintainLLM-powered applicationsand multi-agent systems primarily usingLangGraphandLangChain , alongside tools such as CrewAI or similar frameworksDevelop and optimiseRAG pipelines , including document ingestion, chunking strategies, embedding generation, retrieval logic, and vector searchImplement and manage vector databases such aspgvector on Aurora, OpenSearch, Pinecone , or similarBuild and maintain data and ETL pipelines usingApache Airflow, Prefect , or similar toolsDevelop backend services and APIs inPython / FastAPIto serve AI models, RAG systems, and agent workflowsDeploy and manage AI workloads onAWSservices such asBedrock, SageMaker, Lambda, S3, Aurora/RDS, EC2Work withDocker and Kubernetesto containerise and orchestrate AI workloadsDesign and execute evaluation frameworks for LLM outputs, including automated testing, LLM-as-judge approaches, and human-in-the-loop reviewWork with LLM APIs and orchestration tools such asAWS Bedrock, OpenAI API, Anthropic API , or similarApply prompt engineering and LLM evaluation methodologies,



and assess when fine-tuning or other adaptation techniques are appropriate.Collaborate with domain experts, Data Engineers, Product Managers, and the Tech Lead to turn business requirements into AI solutionsParticipate in Scrum ceremonies and contribute to a collaborative Agile engineering cultureStay up to date with the rapidly evolving AI/ML ecosystem and proactively propose new tools, improvements, and approachesSupport less experienced team members and share AI engineering best practices across the team.Must Have3–5 years of experience in Software Engineering , with at least1–2 years focused on AI / ML EngineeringStrong proficiency inPythonExperience with AI/ML and LLM frameworks such asLangChain, LangGraph, Hugging Face, PyTorch , or similarHands-on experience buildingRAG systems , including embeddings, vector stores, semantic search, and hybrid search strategiesExperience working withLLM APIssuch asAWS Bedrock, OpenAI API, Anthropic API , or similarSolid understanding ofprompt engineering, fine-tuning techniques, and LLM evaluation methodologiesHands-on experience withAWSservices such asEC2, S3, Lambda, Aurora/RDS, Bedrock, SageMakerExperience with observability and evaluation platforms for LLMs such asLangfuse, Datadog LLM Observability, LangSmithExperience withDocker and KubernetesFamiliarity with data pipeline tools such asApache Airflow, Prefect , or similarExperience developing backend services or APIs, ideally withFastAPIProficiency withGitand software engineering best practicesExperience working in aScrum AgileenvironmentStrong problem-solving, analytical thinking, communication, and teamwork skillsFluentEnglishNice to HaveExperience withmulti-agent architecturesand protocols such asA2A or MCPFamiliarity with MLOps practices: model versioning, experiment tracking, MLflow, Weights & Biases,



and CI/CD for MLKnowledge of graph databases or knowledge graphs for enhanced retrievalExperience with CI/CD pipelines using tools such asGitHub ActionsFamiliarity with Infrastructure as Code, especiallyTerraformExperience with code quality and security tools such asSonarCloud, SnykExperience in aviation, travel, or large-scale digital environmentsSpanish language skills are a plusHybrid model - 2 days onsite per weekWhy join this project?People first – diverse and inclusive culture in an international environment.Build production-ready LLM applications, RAG systems, and agentic AI solutionsWork 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 AuroraBe part of a fast-moving AI environment where experimentation, ownership, and impact are highly valuedHigh 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, integral events, and strong tech communities.Want to know more about us?Clickhereand discover all the details.Curious about our culture?Check out what people are saying about us onGlassdoor .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. xkdbapo Compliance with internal security and information protection policies is mandatory.

📌 AI Engineer (Barcelona)
🏢 Capitole
📍 Barcelona