DevOps Engineer

Responsibilities

. Design, implement, and maintain cloud infrastructure using Terraform and IaC principles.

. Build and manage AI platform environments across Azure, AWS,

. Develop reusable Terraform modules and infrastructure standards.

. Implement infrastructure automation to improve scalability, reliability and operational efficiency.

. Design and maintain CI/CD pipelines using Azure DevOps, GitHub Actions, GitLab CI, or Jenkins.

. Automate build, test, deployment, and release processes for AI and application workloads.

. Implement GitOps and DevSecOps best practices.

. Support deployment and lifecycle management of AI/ML and Generative AI applications.

. Build and maintain MLOps capabilities including model deployment, versioning, monitoring, and governance.

. Enable integration with AI services such as Azure OpenAI, OpenAI APIs, Azure AI Services, AWS Bedrock, or Vertex AI.

. Deploy and manage containerized workloads using Docker and Kubernetes.

. Maintain scalable Kubernetes environments for AI and enterprise applications.

. Troubleshoot performance, security, and reliability issues within container platforms.

. Implement cloud security best practices, IAM, secrets management, and compliance controls.

. Ensure platform reliability, observability, logging, and monitoring.

. Collaborate with security and governance teams to enforce enterprise standards.

Requirements

. Diploma or Degree in Information Technology, Computer Engineering, or related discipline.

. Minimum 3+ years of experience in Cloud Engineering, Platform Engineering, DevOps, or

Infrastructure Automation.

. Hands-on experience with Terraform and Infrastructure as Code.

. Strong experience designing and managing CI/CD pipelines.

. Experience with Docker and Kubernetes.

. Proficiency in at least one cloud platform: Azure or AWS

. Experience with scripting languages such as Python, PowerShell, Bash, or Shell scripting.

. Strong understanding of Git, version control, and software delivery best practices.

. Experience supporting AI/ML platforms and MLOps environments.

. Knowledge of LLMs, Generative AI

. Experience with: Azure OpenAI Service, Azure Machine Learning, AWS Bedrock

. Knowledge of monitoring and observability tools such as Prometheus, Grafana, Azure Monitor,

Datadog, or Splunk.

. AI, Cloud, Kubernetes, Terraform, or DevOps certifications are advantageous.

. Well verse in DevOps, GitHub Action, GitLab CI/CD, Jenkins, Gits, Docker, Kubernetes

Licence no: 12C6060