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# AI Engineer

- **Company:** Banco Santander, S.A.
- **Location:** Madrid, Spain
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Memory Management, Language Modeling, Cloud Services, Software Engineering, Large Language Models, Multi-Agent Systems, Production Code, Restful APIs
- **Published:** July 13, 2026
- **Apply:** https://es.trabajo.org/oferta-3206-e14d943147be35444a3a63124903de73

## About the Role

graceful failure recovery. (Required) Experience fine-tuning or adapting language models (SFT, LoRA, RLHF) for domain-specific tasks, including dataset curation and evaluation design. (Required) Track record of delivering complete systems independently within tight timelines - from architecture decision to production-ready code. Portfolio of real systems, not just demos. (Required) Experience building and consuming REST APIs and integrating AI systems with enterprise data sources, cloud services and third-party platforms. (Required) Prior experience in banking, fintech, or other regulated industries. (Preferred) Exposure to Harness Engineering methodologies: spec-driven development, AI-assisted software creation at scale. (Preferred) Education Bachelor's or Master's degree in Comp

## Description

that can be handed off to the AI Science team for production scaling. You own your code end-to-end. 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 are 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 4-8 years of software engineering or AI engineering experience, with at least 2 years building and maintaining LLM-powered systems in production environments - not in notebooks. (Required) Demonstrated hands-on experience designing and deploying multi-agent AI systems with real-world complexity: memory management, stateful orchestration, tool use, multi-step planning, and


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