Artificial Intelligence Engineer

Role - AI EngineerLocation: Europe (Madrid, Spain preferred - travel to Spain customer site ideally once a month)Language: Fluency in both English and Spanish requiredLos candidatos deben tomarse el tiempo de leer atentamente todos los elementos de este anuncio de empleo. Por favor, envíen su solicitud sin demora.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 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. xbhjioeAdditional GCP certifications (e.g., Professional Cloud Architect, Data Engineer).CertificationGoogle Cloud Professional Machine Learning Engineer certification (Good To have)

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. xbhjioe Additional GCP certifications (e.g., Professional Cloud Architect, Data Engineer). Certification Google Cloud Professional Machine Learning Engineer certification (Good To have)