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.
Key Responsibilities
- 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.
Requirements
- 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.
Preferred Skills
- Kubernetes Administration
- GitHub Actions / GitLab CI / Jenkins
- MLOps and AI Platform Operations
- Infrastructure Automation
- Cloud Security & DevSecOps
- Generative AI Platform Deployment