DevOps Engineer

DevOps Engineer (GitOps / Kubernetes / AWS)

Location: Columbus, OH (Onsite)

Job Type: Contract-to-Hire

About the Role

Our 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, GCP)

Experience with advanced monitoring and observability practices

Exposure to agentic/AI-driven automation systems