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DevOps Engineer

Summary

Designs and maintains cloud infrastructure and CI/CD pipelines for AI platforms using Terraform, Kubernetes, and Azure/AWS. Builds MLOps and GenAI deployment workflows with GitOps and DevSecOps practices.

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

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