AIOps Engineer - AWS

Can you imagine building the cloud platform that enables AI, RAG and intelligent agents to operate reliably at scale?

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Join our expert team to work on a Sector focused on Business Intelligence, contributing to the development of Solution for AI and Data Platform operations.

You will apply your knowledge of AWS, Python, Terraform and MLOps to evolve cloud infrastructure, support AI workloads and improve observability, reliability and scalability.

How do we make this happen?

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 at ERNI. 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.

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.

What you will bring

Strong hands-on experience working with AWS environments and cloud infrastructure.

Solid experience with Python and Infrastructure as Code using Terraform or AWS CDK.

Experience with MLOps, AIOps or Data Platform environments including monitoring, troubleshooting and observability.

Knowledge of AI integrations including RAG, LLMs, Claude / Anthropic API or MCP.

English level B2 or higher and experience working with Jira, Confluence and Bitbucket.

You will be responsible for designing, deploying and evolving AWS infrastructure for AI and data environments while improving cost, performance and security. Supporting AI and Data teams by troubleshooting pipelines and execution environments. Enabling RAG and AI agent integrations and improving observability through logs, metrics and proactive monitoring. Developing internal Python tools, libraries and reusable frameworks.

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 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 other's faces; the best stories always happen in the office!

You will also enjoy:

And the salary? xcskxlj

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