AI Software Engineering Analyst

Country: Spain

IT STARTS HERE

Santander (*****************) is evolving from a general, 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 what’s possible.

This is more than a strategic shift. It’s 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.

Our Chief Data & Artificial Intelligence Officer (CDAIO) division is building a world-class AI & Data team to make a difference in the lives of over 170 million people worldwide, through one of the largest banks in the world.

We are undergoing one of the biggest transformations in our history and technology is at the heart of our strategy. Join our team to play a part in one of the most important technological projects for the financial sector in the world.

Our mission is to contribute to helping 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.

THE DIFFERENCE YOU MAKE

CDAIO/ AI TECH is looking for a AI Software Engineering Specialist based out of Madrid.

You will be responsible for designing, developing, and implementing AI-driven solutions that accelerate software delivery, improve software quality, and automate engineering and operational processes across the development ecosystem.

This is a highly technical role requiring deep expertise across software architecture,



application development, DevOps, cloud platforms, and AI-enabled engineering practices.

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 and develop deterministic agents and intelligent automation systems focused on software engineering use cases.

- Implement AI-powered solutions to automate SDLC activities, including:code generation and review, automated testing, technical documentation, quality analysis, incident management, CI/CD pipelines, observability and operations.

- Design scalable, resilient, and secure software architectures in cloud environments.

- Contribute to architecture decisions and technical standards.

- Develop modern backend and frontend applications.

- Integrate AI/LLM capabilities into enterprise platforms and engineering workflows.

- Define and promote best practices in software engineering, security, observability, and automation.

- Collaborate with multidisciplinary teams across engineering, infrastructure, architecture, and business domains.

- Lead innovation initiatives related to AI-enabled software engineering.

- Evaluate emerging AI technologies, frameworks, and tooling.

WHAT YOU’LL BRING

Our people are our greatest strength. Every individual contributes unique perspectives that make us stronger as a team and as an organization.



We’re 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 across: software architecture, technical design, backend/frontend development, systems integration, testing, deployment, DevOps, application operations.

- Hands-on experience building: deterministic agents, automated workflows, AI-based systems, engineering assistants, automation platforms.

- 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 experience with public cloud platforms: AWS, Azure. (Required)

- Advanced experience with several modern s...

📌 AI Software Engineering Analyst (Madrid)
🏢 Banco Santander
📍 Madrid