MLOps & AI Deployment Engineer

SUNDUS MANAGEMENT CONSULTANCY & STUDIES BUREAUL.L.C; Abu Dhabi; On-site; AED 280,000 - 420,000; Full time

Job summary

SUNDUS MANAGEMENT CONSULTANCY & STUDIES BUREAUL.L.C seeks an experienced DevOps/Platform Engineer to design and maintain infrastructure. You will manage compute, Linux environments, and cloud/on-prem resources, enabling robust development and AI workloads.

The role emphasizes Docker/Kubernetes, CI/CD pipelines, and collaboration with AI engineers to operationalize models and ensure system reliability across environments.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related field.
• 7+ years of experience in DevOps or platform engineering roles.
• Basic to intermediate experience with Linux system administration.
• Hands-on experience with Docker and containerization.
• Familiarity with Kubernetes (deployment and basic management).
• Experience with CI/CD tools (Azure DevOps, GitHub Actions, Jenkins, etc.).
• Basic understanding of cloud platforms (Azure, AWS, or GCP).
• Scripting skills in Python, Bash, or similar.
• Understanding of version control systems (Git).
• Exposure to AI/ML model deployment and MLOps practices.

Responsibilities

• Set up and maintain compute infrastructure including GPU-enabled environments.
• Configure and manage Linux-based systems for development and production environments.
• Provisioning and configuration of cloud and on-prem infrastructure.

Skills

Linux administration

Python scripting

Bash scripting

Git (version control)

Microservices architecture

Education

Bachelor’s degree in Computer Science, Engineering, or related field

Tools

Docker

Kubernetes

Azure DevOps

GitHub Actions

Jenkins

Terraform

ARM templates

Prometheus

Grafana

ELK

Job description

SUNDUS MANAGEMENT CONSULTANCY & STUDIES BUREAUL.L.C seeks an experienced DevOps/Platform Engineer to design and maintain infrastructure. You will manage compute, Linux environments, and cloud/on-prem resources, enabling robust development and AI workloads.

The role emphasizes Docker/Kubernetes, CI/CD pipelines, and collaboration with AI engineers to operationalize models and ensure system reliability across environments.