AI Infrastructure Engineer

Join our expert team to work on an Enterprise platform, contributing to the development of scalable AI infrastructure and shared services for enterprise AI adoption. You will apply your knowledge of Kubernetes , LLMOps , AI governance , model routing, RAG services , and platform engineering to create a secure, reliable, and cost-efficient AI ecosystem used by multiple teams globally. Even if you work on an external project, you will feel part of the team and always supported. You will have regular 1:1 meetings with them, and recurrently, you will work on your development plan to define your short-, medium-, and long-term goals. As a senior profile, you will have the space to continue growing, whether by deepening your technical skills or having greater influence on project decisions, with autonomy and the opportunity to share knowledge with other experts. Strong expertise in Kubernetes, cloud-native infrastructure, networking, and platform operations.
• Experience with LLMOps/MLOps ecosystems, vector databases, embeddings, RAG architectures, and AI frameworks.
• Hands-on software engineering experience with Python, Java, Infrastructure as Code with Terraform, and CI/CD practices.
• What if the project ends? We work on a wide variety of projects, technologies, and sectors, allowing you to keep growing in different environments. If a project ends or you feel ready for a new challenge, we will find another one that aligns with your professional development. We trust you to deliver quality work within your 40-hour workweek. Our model is hybrid: we usually go to the office 2 days a week, though this depends on the project and team, but we love seeing each other’s faces; the best stories always happen in the office Private health insurance. Free emotional, legal, and family support. ️‍♀️ English, Spanish, Catalan and German. We will discuss it during the first call. If it is important to you, feel free to ask