GCP Devops Engineer

THE DIFFERENCE YOU MAKE

CDAIO/ AI TECH is looking for a GOOGLE CLOUD PLATFORM DEVOPS ENGINEER based out of Madrid.

You will play a key role in enabling the design, development, and deployment of scalable and resilient AI solutions. Your mission will be to build and maintain the infrastructure and automation pipelines that support the entire AI lifecycle—from experimentation to production—ensuring agility, security, and operational excellence.

You will work in close collaboration with AI Experts, Data Scientists, ML Engineers, and enterprise technology partners to accelerate the delivery of AI products that drive business value across Santander. This is a critical role in the AI transformation agenda, empowering the team to deliver responsible AI at scale.

We’re shaping the way we work through innovation, cutting‑edge technology, collaboration and the freedom to explore new ideas. To succeed in this role, you will be responsible for:

• Design, implement, and manage robust CI/CD pipelines for AI/ML models and GenAI applications.
• Build and maintain cloud-native infrastructure (GCP) to support the full AI lifecycle: from data ingestion and model training to production deployment and monitoring.
• Automate infrastructure provisioning using Infrastructure as Code (IaC) tools such as Terraform, or InfraManager.
• Implement a robust FinOps strategy across the entire stack to ensure proper cost attributions and traceability across the entire infrastructure.
• Design and implement world‑class networking and security cloud architectures, aligned with Banco Santander’s existing stack.
• Ensure scalability, reliability, and high availability of AI services in production environments.
• Implement and enforce best practices in MLOps, including model versioning, monitoring, rollback, and automated testing.
• Collaborate with data engineering and ML teams to operationalize AI models and integrate them into business‑critical systems.
• Monitor system performance, debug issues, and lead root‑cause analysis and resolution of incidents.
• Champion security, compliance, and governance standards across the AI tech stack.
• Contribute to the continuous improvement of DevOps capabilities and tooling within the AI Tech Team.
• Seek for excellence in the utilization of cloud native capabilities, always looking for continuous improvements in all we do.
• Act as a technical advisor in DevOps and MLOps practices, fostering a culture of automation and engineering excellence.
• Embracing the continuous learning culture of the CDAIO / AI Tech team.
• Acting as a facilitator for all the teams & entities that use the infrastructure, working and collaborating with them hand in hand.

WHAT YOU’LL BRING

The following requirements represent the knowledge, skills, and abilities essential for success in this role. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Professional Experience

• 5+ years of experience in DevOps, Site Reliability Engineering, or Platform Engineering roles. (Required)
• Proven experience supporting ML/AI workloads in production environments. (Required)
• Hands‑on experience with containerization (Docker, Kubernetes) and orchestration of microservices. (Required)
• Strong background in managing cloud environments (AWS or GCP), including cost optimization and security best practices. (Required)
• Solid experience implementing CI/CD pipelines and using...