Cloud AI Platform & MLOps Engineer

Verisure; Elche; On-site; EUR 55,000 - 90,000; Full time

Job summary

Verisure is seeking an AI Engineer to join its Data & AI team, focused on building and scaling the platform behind AI products. The role emphasizes platform engineering, automation, observability, and operations rather than building models.

You will work with cloud technologies (AWS, with Azure exposure) and collaborate with Data Scientists, Data Engineers, and Product teams to productionize AI solutions. A strong foundation across the AI ops stack is valued, with growth opportunities across the

Qualifications

• Experience in MLOps, AIOps, or operating ML systems in production.
• Strong background in cloud (AWS and/or Azure).
• Hands-on with Docker, Kubernetes, and CI/CD pipelines.
• Experience with monitoring & observability tools.
• Knowledge of LLMs, RAG pipelines, or AI agents.
• Solid Python skills and understanding of ML lifecycle.

Responsibilities

• Design, build, and evolve our AI operations platform.
• Operate and optimize ML and LLM pipelines (RAG, agents, etc.).
• Ensure reliability, scalability, and observability of AI systems.
• Monitor model performance, quality, and drift.
• Manage deployments in AWS/Azure with Docker & Kubernetes.
• Implement LLMOps / AgentOps practices (evaluation, logging, orchestration).
• Drive automation, CI/CD, and infrastructure as code.
• Partner with cross-functional teams to bring AI solutions into production.

Skills

MLOps

AIOps

Cloud - AWS

Cloud - Azure

Docker

Kubernetes

CI/CD

Observability

LLMs

RAG

AI agents

Python

Tools

SageMaker

Azure ML

MLflow

Kubeflow

LangChain

LlamaIndex

Job description

Verisure is seeking an AI Engineer to join its Data & AI team, focused on building and scaling the platform behind AI products. The role emphasizes platform engineering, automation, observability, and operations rather than building models.

You will work with cloud technologies (AWS, with Azure exposure) and collaborate with Data Scientists, Data Engineers, and Product teams to productionize AI solutions. A strong foundation across the AI ops stack is valued, with growth opportunities across the