MLOps Engineer – AI & LLM Platforms

About the role

The MLOps Engineer will design, automate and maintain the infrastructure and deployment pipelines that support AI/ML and micro‑services applications, including large language model (LLM) workloads. Working in Abu Dhabi, you will enable fast, reliable delivery of AI solutions while ensuring scalability, performance and system health.

Key responsibilities

• Set up and manage GPU‑enabled compute environments and Linux‑based development/production systems.
• Provision cloud and on‑prem resources using Infrastructure‑as‑Code tools (Terraform, ARM templates).
• Build, containerise and deploy applications with Docker and Kubernetes, creating Helm charts and environment configurations.
• Develop and maintain CI/CD pipelines in Azure DevOps, GitHub Actions or Jenkins for code and model promotion across dev, test and prod.
• Deploy, version and monitor machine‑learning models and LLM services, supporting RAG pipelines and inference APIs.
• Implement monitoring and logging solutions (Prometheus, Grafana, ELK) and respond to incidents, performing root‑cause analysis.
• Automate repetitive operational tasks with Python and Bash scripts.

Required profile

• 7+ years of experience in DevOps/MLOps engineering.
• Strong background in Linux system administration and cloud platforms.
• Proven experience deploying AI/ML models and managing GPU workloads.
• Ability to troubleshoot pipeline failures and production incidents.

Required skills

• Docker
• Kubernetes
• Terraform
• ARM templates
• Python
• Bash
• Git, GitHub Actions
• Azure DevOps
• Jenkins
• Prometheus
• Grafana
• ELK stack
• Infrastructure as Code
• Linux system administration