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# Ai Engineer

- **Company:** Capitole
- **Location:** Madrid, Spain
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Automation of Tests, Cloud Computing, Software Quality, Cyber Security, Continuous Integration, Extract Transform Load (ETL), DevOps, Github, Graph Database, Python (Programming Language), Machine Learning, Scrum Methodology, Search Technologies, Software Construction, Software Engineering, Datadog, Pytorch, Large Language Models, Multi-Agent Systems, Prompt Engineering, Backend, Git, Fastapi, AI Platforms, HuggingFace, Machine Learning Operations, Functional Programming, Api Design, Terraform, GPT, Software Version Control, Data Pipelines, Docker
- **Published:** August 5, 2026
- **Apply:** https://www.buscojobs.com.es/ai-engineer-en-madrid-ID-365576094

## About the Role

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 observability and evaluation platforms for LLMs such as
Langfuse, Datadog LLM Observability, LangSmith
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
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
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

## Description

We 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.3-5 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 skillsExperience 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 ecosystemContribute to scalable engineering practices around AI applications, data pipelines, evaluation, and deploymentGain 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.€**** per year training budget and continuous learning opportunities.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.Information Security NoticeThe employee will have access to confidential information related to Capitole and the assigned project.Compliance with internal security and information protection policies is mandatory.#J-*****-Ljbffr


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