Location: Columbus, OH
Salary: $65.00 USD Hourly - $70.00 USD Hourly
Description: DevOps Engineer (GitOps / Kubernetes / AWS)Location: Columbus, OH (Onsite)
Job Type: Contract-to-Hire
About the RoleOur client is seeking a highly skilled
DevOps Engineer to design, build, and maintain cloud-native infrastructure and automation solutions. This role requires strong expertise in
Kubernetes, GitOps, Terraform, and AWS, along with experience developing automation tools using Python.
You will play a critical role in enabling scalable, reliable, and secure systems, including support for
modern ML platforms and pipelines.
Key Responsibilities - Design, develop, and maintain cloud-native infrastructure using Kubernetes, Docker, and AWS services (EKS, ECS, ECR)
- Implement and manage GitOps workflows for continuous deployment and environment consistency
- Build and maintain Infrastructure as Code (IaC) using Terraform
- Develop Python-based automation tools to improve operational efficiency and system reliability
- Design and support CI/CD pipelines using tools such as Jenkins and GitLab CI
- Deploy and manage applications in Kubernetes environments using Helm
- Implement monitoring and observability using Prometheus and Grafana
- Identify and automate remediation of recurring operational issues
- Collaborate with cross-functional teams to review architecture, evaluate tools, and drive technical decisions
- Contribute to the design and development of scalable ML platforms, including training, deployment, and monitoring pipelines
Required Qualifications - Bachelor's degree in Computer Science, Engineering, or related field (required)
- Hands-on experience with Kubernetes and Docker in production environments
- Strong knowledge of GitOps practices (e.g., ArgoCD, Flux)
- Expertise in Terraform (Infrastructure as Code)
- Experience with AWS services, especially EKS, ECS, and ECR
- Proficiency in Python for automation and tooling
- Experience building and managing CI/CD pipelines
- Strong understanding of cloud-native architecture and deployment strategies
- Solid debugging, troubleshooting, and system design skills
Preferred Qualifications (Nice to Have) - Experience with MLOps or AI/ML platforms (Kubeflow, model pipelines)
- Knowledge of deployment strategies (Blue/Green, Canary, Rolling)
- Familiarity with multi-cloud environments (AWS, Azure, Google Cloud Platform)
- Experience with advanced monitoring and observability practices
- Exposure to agentic/AI-driven automation systems
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