Lead DevOps Engineer

Design, implement, and maintain cloud-native infrastructure using Terraform, Helm, and Kubernetes across development, staging, and production environments.

Develop and maintain GitLab CI/CD pipelines for automated builds, tests, and deployments.

Build and manage containerized workloads using Docker and Kubernetes, ensuring proper configuration, scaling, and observability.

Automate configuration management tasks with Ansible and ensure system consistency across environments.

Write robust Python and Shell scripts for automation, orchestration, monitoring, and system maintenance tasks.

Work closely with development teams to support application deployment, monitoring, logging, and operational troubleshooting.

Ensure system security and compliance through automated tooling and infrastructure policies.

Monitor system performance and implement proactive solutions to improve availability, scalability, and resilience.

Document infrastructure design, operational procedures, and runbooks to support team onboarding and knowledge sharing.

Participate in on-call rotations and incident response as needed.

Business trip to Kuwait

Bachelor's degree in Computer Science, Engineering, or a related technical field.

10+ years of experience in DevOps, SRE, or infrastructure engineering roles in cloud-native environments.

Proficient in Python and Shell scripting for automating operational tasks and infrastructure logic.

Strong hands-on experience with Ansible for configuration management and Terraform for infrastructure as code.

Solid understanding and usage of Kubernetes, Helm, and Docker for container orchestration and management.

Experience implementing and optimizing CI/CD pipelines using GitLab or similar platforms.

Familiarity with observability and monitoring tools (e.g., Prometheus, Grafana, New Relic).

Experience managing secrets, certificates, and environment configurations securely.

Deep understanding of networking concepts, system-level security, and Linux administration.

Strong troubleshooting and debugging skills across the stack (infrastructure, OS, containers, and applications).

Excellent communication skills and the ability to work collaboratively across teams.

Knowledge or hands-on experience in AI/ML infrastructure, including model deployment, serving, or pipeline automation.

Familiarity with cloud platforms such as Azure or AWS.

Experience with GitOps tools (e.g., Argo CD, Flux).

Background in supporting enterprise applications in oil and gas, energy, or other industrial domains.