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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Artificial Intelligence Engineer - **Company:** Quantiphi - **Location:** Guntín, Spain - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, BigQuery, Cloud Computing, Computer Programming, Databases, Continuous Integration, Data Structures, Database Development, Software Design Patterns, Linux, DevOps, Python (Programming Language), Linux System Administration, Machine Learning, Search Technologies, Software Engineering, Google Cloud, Delivery Pipeline, Large Language Models, Multi-Agent Systems, Multi-Cloud, Kubernetes, Infrastructure Automation Frameworks, Data Management, Machine Learning Operations, Virtual Agents, Software Coding, Docker - **Published:** August 19, 2026 - **Apply:** https://www.buscojobs.com.es/artificial-intelligence-engineer-en-guntin-ID-367844597 ## 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 required Required 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 Skills GCP Stack (Mandatory): AlloyDB, Google Cloud Storage (GCS), Google Kubernetes Engine (GKE) Gemini Enterprise, Agent Platform (formerly Vertex AI) BigQuery, Cloud Run, Vertex AI Pipelines Programming: 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 Have Experience 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). Certification Google 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 required Required 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 Skills GCP Stack (Mandatory): AlloyDB, Google Cloud Storage (GCS), Google Kubernetes Engine (GKE) Gemini Enterprise, Agent Platform (formerly Vertex AI) BigQuery, Cloud Run, Vertex AI Pipelines Programming: 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 Have Experience 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).Certification Google Cloud Professional Machine Learning Engineer certification (Good To have) ## Related Videos - [Docker network without Docker](https://www.wearedevelopers.com/videos/1418-docker-network-without-docker) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [AI Agents & Agentic AI](https://www.wearedevelopers.com/videos/2017-ai-agents-agentic-ai) - [Docker exec without Docker](https://www.wearedevelopers.com/videos/1094-docker-exec-without-docker) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [Got AI ideas but no money? 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