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# Artificial Intelligence Engineer

- **Company:** Quantiphi
- **Location:** Santander, Spain
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, BigQuery, Cloud Computing, Databases, Continuous Integration, Data Structures, Linux, DevOps, Python (Programming Language), Machine Learning, Search Technologies, Software Engineering, Large Language Models, Multi-Agent Systems, Multi-Cloud, Kubernetes, Infrastructure Automation Frameworks, Data Management, Machine Learning Operations, Software Coding, Docker
- **Published:** August 19, 2026
- **Apply:** https://www.buscojobs.com.es/artificial-intelligence-engineer-en-santander-ID-367883712

## About the Role

Role - AI Engineer Location: Europe (Madrid, Spain preferred - travel to Spain customer site ideally once a month)Language: Fluency in both English and Spanish requiredRequired Skills and Experience: 5+ years of experience designing, developing, and deploying high-performance data platforms and agentic solutions.Proven experience in designing cloud enterprise solutions and supporting customer projects through completion.Strong proficiency in the GCP stack: AlloyDB, GCS, GKE, Gemini Enterprise, and Agent Platform (formerly Vertex AI).
Advanced Python coding skills, including data structures, algorithms, and software design.Experience in automating infrastructure provisioning, DevOps/MLOps, and CI/CD.Google Cloud Professional ML Engineer certification.Technical SkillsGCP Stack (Mandatory):AlloyDB, Google Cloud Storage (GCS), Google Kubernetes Engine (GKE)Gemini Enterprise, Agent Platform (formerly Vertex AI)BigQuery, Cloud Run, Vertex AI PipelinesProgramming: Advanced Python skills including data structures, algorithms, and software design patterns.Agentic AI: Hands-on experience with AI Agents, Agent Development Kit (ADK), multi-agent frameworks, and RAG integration.MLOps/DevOps: Experience with Kubeflow, Docker, Kubernetes, and Linux environments.CI/CD: Proficiency in building and managing continuous integration and deployment pipelines.GenAI/LLM: Experience with LLMs, GenAI APIs, Model Garden, and GenAI Studio.Good to HaveExperience with AlloyDB and enterprise database solutions.Familiarity with PaLM embeddings and
vector search technologies.Exposure to multi-cloud environments.Prior experience in healthcare, retail, or financial services domains.Additional GCP certifications (e.g., Professional Cloud Architect, Data Engineer).
CertificationGoogle Cloud Professional Machine Learning Engineer certification (Good To have)

## Description

Role - AI Engineer Location: Europe (Madrid, Spain preferred - travel to Spain customer site ideally once a month)Language: Fluency in both English and Spanish requiredRequired Skills and Experience: 5+ years of experience designing, developing, and deploying high-performance data platforms and agentic solutions.Proven experience in designing cloud enterprise solutions and supporting customer projects through completion.Strong proficiency in the GCP stack: AlloyDB, GCS, GKE, Gemini Enterprise, and Agent Platform (formerly Vertex AI).Advanced Python coding skills, including data structures, algorithms, and software design.Experience in automating infrastructure provisioning, DevOps/MLOps, and CI/CD.Google Cloud Professional ML Engineer certification.Technical SkillsGCP Stack (Mandatory):AlloyDB, Google Cloud Storage (GCS), Google Kubernetes Engine (GKE)Gemini Enterprise, Agent Platform (formerly Vertex AI)BigQuery, Cloud Run, Vertex AI PipelinesProgramming: Advanced Python skills including data structures, algorithms, and software design patterns.Agentic AI: Hands-on experience with AI Agents, Agent Development Kit (ADK), multi-agent frameworks, and RAG integration.MLOps/DevOps: Experience with Kubeflow, Docker, Kubernetes, and Linux environments.CI/CD: Proficiency in building and managing continuous integration and deployment pipelines.GenAI/LLM: Experience with LLMs, GenAI APIs, Model Garden, and GenAI Studio.Good to HaveExperience with AlloyDB and enterprise database solutions.Familiarity with PaLM embeddings and vector search technologies.Exposure to multi-cloud environments.Prior experience in healthcare, retail, or financial services domains.Additional GCP certifications (e.g., Professional Cloud Architect, Data Engineer).CertificationGoogle Cloud Professional Machine Learning Engineer certification (Good To have)


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