MLOps Engineer – AI & LLM Platforms

About the role

The MLOps Engineer will design, automate, and maintain the infrastructure and deployment pipelines that power AI/ML and micro‑service applications, including large‑language‑model (LLM) workloads. You will enable fast, reliable development, testing, and production of AI solutions while ensuring scalability and performance.

Key responsibilities

• Provision and manage GPU‑enabled compute environments on‑premise and in the cloud.
• Configure Linux systems for development and production, and monitor resource usage.
• Build, containerize, and deploy applications using Docker and Kubernetes, creating Helm charts and environment configurations.
• Develop and maintain CI/CD pipelines with Azure DevOps, GitHub Actions, or Jenkins, automating build, test, and release processes.
• Deploy, version, and monitor machine‑learning models and LLM services, supporting RAG pipelines and inference endpoints.
• Implement observability stacks (Prometheus, Grafana, ELK) to track performance, health, and availability.
• Write automation scripts in Python and Bash, and support IaC initiatives with Terraform or ARM templates.
• Collaborate with senior DevOps/MLOps engineers, AI engineers, and development teams to troubleshoot issues and improve workflows.

Required profile

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• 7+ years of experience in DevOps, platform engineering, or related roles.
• Strong hands‑on experience with Linux system administration.
• Proven track record delivering containerized solutions at scale.

Required skills

• Docker
• Kubernetes (deployment, Helm)
• Azure DevOps, GitHub Actions, Jenkins
• Python, Bash scripting
• Terraform, ARM templates (IaC)
• Prometheus, Grafana, ELK stack
• GPU‑enabled infrastructure provisioning

What we offer

• One‑year renewable contract with competitive compensation.
• Opportunity to work on cutting‑edge AI and LLM platforms.
• Collaboration with a high‑performing technical team in Abu Dhabi.