DevOps Engineer (AL-FNC1)

We are looking for an experienced DevOps Engineer to design build and maintain scalable AI platforms that support enterprise AI Machine Learning and Generative AI initiatives. This role combines Cloud Engineering DevOps Platform Engineering and MLOps making it ideal for candidates passionate about automation Kubernetes cloud-native technologies and AI platform operations.

You will work closely with cloud architects infrastructure teams and application developers to deliver secure scalable and highly available AI platforms.

• Design implement and manage cloud infrastructure using Terraform and Infrastructure-as-Code (IaC) practices.
• Build and maintain AI platform environments across Azure and AWS.
• Develop and optimize CI/CD pipelines using Azure DevOps GitHub Actions GitLab CI or Jenkins.
• Automate application and platform deployments using DevOps and GitOps methodologies.
• Support AI/ML and Generative AI workloads including deployment monitoring and lifecycle management.
• Manage containerized environments using Docker and Kubernetes.
• Implement platform monitoring logging observability security and governance best practices.
• Support MLOps capabilities including model deployment versioning monitoring and automation.
• Collaborate with engineering security and architecture teams to improve platform reliability and operational efficiency.
• Troubleshoot infrastructure performance security and platform-related issues.

• Diploma or Degree in Information Technology Computer Science Computer Engineering or related discipline.

• Minimum 3 years of experience in DevOps Cloud Engineering Platform Engineering or Infrastructure Automation.
• Strong hands-on experience with Terraform and Infrastructure-as-Code.
• Experience building and maintaining CI/CD pipelines.
• Strong knowledge of Docker and Kubernetes.
• Hands-on experience with Azure and/or AWS cloud platforms.
• Scripting experience in Python PowerShell Bash or Shell scripting.
• Knowledge of Git version control and DevOps best practices.
• Experience supporting AI/ML platforms MLOps environments or Generative AI workloads is highly advantageous.
• Familiarity with Azure OpenAI Azure Machine Learning AWS Bedrock or similar AI services is a plus.
• Experience with monitoring tools such as Prometheus Grafana Datadog Splunk or Azure Monitor.
• Cloud Kubernetes Terraform DevOps or AI-related certifications are advantageous.

• Kubernetes Administration
• GitHub Actions / GitLab CI / Jenkins
• MLOps and AI Platform Operations
• Infrastructure Automation
• Cloud Security & DevSecOps
• Generative AI Platform Deployment

Required Experience:

IC