Devops Engineer
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Santander ( ) is evolving from a global, high-impact brand into a technology-driven organization, and our people are at the heart of this journey. Together, we are driving a customer-centric transformation that values bold thinking, innovation, and the courage to challenge whats possible.
This is more than a strategic shift. Its a chance for driven professionals to grow, learn, and make a real difference.
Our mission is to contribute to help more people and businesses prosper. We embrace a strong risk culture and all our professionals at all levels are expected to take a proactive and responsible approach toward risk management.
Santander Digital Services is the team of technology and operations at Santander. We are convinced of the importance of technology that is aligned with the requirements of the business and that out work not only brings value to users, people and communities but also fosters individual creativity. Our team of over 10,000 people in 8 countries (Spain, Portugal, Poland, UK, USA, Mexico, Chile and Brazil) develops and/or implements financial solutions across a broad spectrum of technologies on all kinds of on-premise and cloud-based platforms.
THE DIFFERENCE YOU MAKE
SANTANDER DIGITAL SERVICES/ AI TECH is looking for a 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.
Were 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 (AWS or 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 CloudFormation.
- 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.
- Act as a technical advisor in DevOps and MLOps practices, fostering a culture of automation and engineering excellence.
WHAT YOULL BRING
Our people are our greatest strength. Every individual contributes unique perspectives that make us stronger as a team and as an organization. Were enabling teams to go beyond by valuing who they are and empowering what they 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 tools such as Jenkins, GitHub Actions, GitLab CI, or similar
- Familiarity with machine learning workflows, model deployment patterns, and MLOps tools (e.g., MLflow, Kubeflow, SageMaker, Vertex AI). (Preferred)
Education
- BSc or MSc in Computer Science, Engineering, or a related technical field. (Required)
- Relevant certifications in cloud platforms or DevOps practices (e.g., AWS DevOps Engineer, Azure DevOps, Google Cloud DevOps). (Preferred)
Languages
- Spanish proficiency. (Required)
- High level of English. (Preferred)
Hard Skills
- Strong scripting and automation skills (e.g., Python, Bash, Go). (Required)
- Experience with monitoring and logging tools (e.g., CloudWatch, Prometheus, Grafana, ELK Stack, Dynatrace). (Required)
- Deep understanding of CI/CD and infrastructure automation principles. (Required)
- Knowledge of security and compliance in cloud-based and AI-driven systems. (Required)
- Experience with application monitoring and logging tools (e.g., Prometheus, Grafana, ELK Stack). (Preferred)
Soft Skills
- Strong problem-solving skills, a deep sense of ownership, and a proactive attitude. xpzdshu
- Excellent communication skills with the ability to lead technical discussions and collaborate effectively with both technical and non-technical stakeholders.
CI/CD, Docker, Kubernetes, AWS, GCP