AI Platform Engineer

***HIRING***

I am looking for an AI Platform Engineer, who has strong skills within K8s & on premises Kubernetes.

This is a 1-year contract, with the view to extend, and will have travel to both Dubai & Abu Dhabi.

Job Title – Ai Platform Engineer

Salary – AED 35,000 – AED 36,000 Per Month

Contract Length – 1 Year Contract with the view to extend

Location – Dubai

Start Date – ASAP

My client is a specialist AI and data consultancy with extensive experience implementing intelligent enterprise systems across multiple industries, with particular depth in financial services and banking.

They need an AI Platform Engineer that helps design, build and maintain the on-premises AI Infrastructure for the end client. As the engineer you will play a key role in enabling large-scale machine learning and generative AI workloads by developing robust, scalable, and secure platform solutions that support data scientists and ML engineers across the organisation.

The role requires deep Kubernetes and infrastructure automation experience to optimise performance, streamline deployments, and ensure reliability in an on-prem environment.

Requirements

• Design, deploy, and manage on-premises Kubernetes clusters for AI and ML workloads.
• Develop and maintain infrastructure-as-code using tools like Terraform, Helm, or Ansible
• Build and optimise AI/ML pipelines and MLOps workflows for model training, deployment, and monitoring.
• Manage containerisation, networking, and storage solutions for AI workloads.
• Ensure security, compliance, and reliability of the AI platform.
• Automate operational processes and continuously improve platform efficiency.

What they need from you:

• Proven experience managing Kubernetes clusters on-premises (not just cloud-managed solutions)
• Strong background in container orchestration, CI/CD, and automation.
• Proficiency in Linux administration, Docker, and networking fundamentals.
• Hands-on experience with infrastructure-as-code (Terraform, Helm, Ansible, etc.).
• Experience supporting AI/ML workloads (e.g., TensorFlow, PyTorch, Hugging Face, Ray, Kubeflow).
• Familiarity with GPU scheduling and resource management on Kubernetes.
• Knowledge of monitoring and logging tools (Prometheus, Grafana, ELK, etc.).

Regards,

Ollie