​Location: Dubai

Duration: Permanent

We’re currently partnered with a leading technology consultancy who are scaling their tech team. They offer a diverse work environment that provide services in the UAE impacting millions of lives. We're currently helping them search for a Site Reliability Engineer to join their ever-growing team. 

Responsibilities:

• Architect, implement, and oversee scalable, high-performance AI and data infrastructure across cloud (AWS) and on-prem environments.

• Utilize automation tools (e.g., Terraform, Ansible) for provisioning, monitoring, and infrastructure optimization.

• Design robust monitoring, alerting, and logging solutions to detect and mitigate potential failures before they impact operations.

• Develop and maintain seamless CI/CD pipelines to accelerate the deployment of AI models and data-driven applications.

• Optimize workflows to enhance efficiency, reduce deployment friction, and maintain system stability.

• Partner with AI researchers, data engineers, and developers to align infrastructure with project needs.

• Act as a bridge between AI, data, and infrastructure teams, ensuring smooth communication and technical alignment.

• Rapidly diagnose and resolve system incidents, conducting thorough root-cause analyses to prevent future issues.

• Establish and refine disaster recovery frameworks to safeguard AI and data assets.

• Implement stringent security protocols to protect AI and data infrastructure, ensuring compliance with industry regulations.

• Perform regular security evaluations, proactively addressing vulnerabilities.

• Identify opportunities to improve system scalability, efficiency, and resilience.

• Stay ahead of emerging trends in AI infrastructure, site reliability engineering, and cloud technologies.

Qualifications & skills:

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.

• 3-5 years experience in a similar role

• Experience with on-premise and cloud platforms (AWS, GCP, Azure) and container orchestration (Kubernetes, Docker).

• Experience with AI and data-specific infrastructure (e.g., GPU clusters, data lakes)

• Understanding of machine learning frameworks and data processing tools (e.g., TensorFlow, PyTorch, Apache Spark).

Apply Now!