AI Infrastructure Engineer - Cloud & LLMOps - Insurance Industry

Can you imagine shaping the AI platform that enables teams worldwide to build and operate enterprise-grade AI solutions?

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.

At ERNI, you are never just a number. Even if you work on an external project, you will feel part of the team and always supported.

With people. Besides your team and manager, you will have several support figures like a godparent, who will help you with the practical and administrative aspects of daily life during your first 6 months.

And the second most important person after you, your mentor, who will guide you through your entire onboarding and career  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.

At ERNI, we highly value experience and technical knowledge. 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. And if you are interested in mentoring, there is also space for that: supporting other ERNIans while still focusing on the technical excellence that sets us apart.

• Proven experience building and operating AI or developer platforms at production scale.
• 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.
• Strong understanding of AI governance, compliance, safety guardrails, observability, reliability, and AI Fin Ops principles.

You will be responsible for designing, building, and operating the enterprise AI platform runtime while enabling teams through shared AI services, governance frameworks, model routing, prompt and skills management capabilities.

You will also ensure scalability, reliability, observability, compliance, and cost efficiency while defining platform standards and collaborating with internal stakeholders to drive AI adoption across the organization.

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 ask you to be available for key meetings. Need to leave for a doctor’s appointment or to pick up your child from school? No problem. 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 others faces; the best stories always happen in the office!

You will also enjoy:

We will discuss it during the first call. If it is important to you, feel free to ask!