MLOps Engineer

Job Code: 6315

Job Title:

Dev Ops / MLOps Engineer (AI & LLM Platforms)

Location:

Abu Dhabi

Contract:

1 year and renewable

Experience:

7+ years

The Dev Ops / MLOps Engineer is responsible for the setup, automation, and maintenance of infrastructure and deployment pipelines for AI/ML and microservices-based applications. This role focuses on enabling efficient development, testing, and deployment of AI solutions, including LLM workloads, while ensuring system reliability, scalability, and performance.

• 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.
• Monitor system resources and assist in performance tuning and optimization.

• Build and manage containerized applications using Docker
  .
• Deploy and manage applications on Kubernetes clusters under guidance from senior engineers.
• Creating deployment configurations, Helm charts, and environment setups.
• Support scaling and orchestration of microservices and AI workloads.

• Develop and maintain CI/CD pipelines for application and AI model deployment.
• Automate build, test, and deployment processes using tools like Azure Dev Ops, Git Hub Actions, or Jenkins
  .
• Ensure smooth promotion of code and models across environments (dev, test, prod).
• Troubleshoot pipeline failures and deployment issues.

• Deploying machine learning models and LLM-based services
  .
• Integration of AI components into production systems.
• Contribute to model versioning, monitoring, and lifecycle management
  .
• Work with AI engineers to operationalize RAG pipelines and inference services.

• Implement and maintain monitoring and logging solutions (e.g.,
  Prometheus, Grafana, ELK
  ).
• Track application performance, system health, and availability.
• Respond to incidents, troubleshoot issues, and elevate when required.
• Assist in root cause analysis and continuous improvement.

• Write scripts (Python, Bash) to automate repetitive operational tasks.
• Support Infrastructure as Code (IaC) initiatives using tools like Terraform or ARM templates
  .
• Improve operational efficiency through automation and tooling.

• Work closely with Senior Dev Ops/MLOps Engineers, AI Engineers, and Development teams
  .
• Support developers in environment setup, debugging, and deployment processes.
• Follow Dev Ops and MLOps best practices and continuously improve operational workflows.

• Bachelor's degree in Computer Science, Engineering, or related field.
• 7+ years of experience in Dev Ops 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 Dev Ops, Git Hub 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
  .
• Familiarity with LLM deployment concepts and tools
  .
• Basic knowledge of GPU environments and high-performance computing
  .
• Experience with monitoring and logging tools (Prometheus, Grafana, ELK).
• Knowledge of Infrastructure as Code (Terraform, ARM templates).
• Understanding of microservices architecture
  .

• Deployment success rate and pipeline stability.
• System uptime and availability.
• Resolution time for incidents and issues.
• Efficiency of CI/CD processes.
• Infrastructure utilization and basic cost optimization.
• Support effectiveness for development and AI teams.

• Reports to: Senior Dev Ops / MLOps Engineer / Platform Lead
• Key Stakeholders:
  • AI Engineers & Data Scientists
  • Backend & Frontend Developers
  • Dev Ops / Platform Team
  • QA & Release Management Teams