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DevOps Engineer (Saudi)

Lucidya | لوسيديا
Riyadh, KSA
Full-time
Entry
Onsite
Discovered 1 weeks ago
CI/CD pipelinesDockerKubernetesCloud infrastructureTerraformAWS or GCP

Full Job Posting

Role overview

Lucidya is scaling infrastructure and automation for its AI-driven products; the DevOps Engineer supports deployment reliability, system scalability, and operational efficiency.

Responsibilities

  • Build, maintain, and improve CI/CD pipelines and deploy containerized applications with Docker and Kubernetes.
  • Support cloud infrastructure management and automation using Infrastructure as Code tools.
  • Implement and maintain monitoring, logging, and alerting solutions.
  • Automate operational tasks and support developers with deployments, environment configuration, and infrastructure requests.
  • Troubleshoot application, deployment, and infrastructure issues, identify causes, and implement solutions.
  • Collaborate to improve performance, reliability, release processes, and security practices.
  • Investigate incidents, escalate complex issues, and document operational workflows.
  • Monitor system health, resolve routine issues, and improve automation and observability.

Experience and working approach

  • 1–3 years of hands-on DevOps, cloud infrastructure, platform engineering, or related experience is required.
  • Practical experience with CI/CD, Docker, Kubernetes, and cloud infrastructure is required.
  • The role calls for proactive troubleshooting, collaboration with developers, a growth-oriented approach, and attention to reliability, security, monitoring, and documentation.

Technical skills

  • CI/CD experience with GitHub Actions, GitLab CI/CD, Jenkins, or similar tools is required.
  • Docker experience and working Kubernetes knowledge, including deployment, configuration, and troubleshooting, are required.
  • Familiarity with Terraform, CloudFormation, or similar tools is required; AWS or GCP experience is required.
  • Basic Bash or Python scripting, monitoring and logging familiarity, configuration management knowledge, Linux, networking, DNS, HTTP/HTTPS, and Git are requested.
  • SaaS or AI experience, production Kubernetes exposure, advanced observability, cloud security, and deployment optimization are advantageous.

First 90 days and success measures

First 30 days: learn the infrastructure, architecture, deployment workflows, tools, and existing cloud and Kubernetes environments.

By 60 days: contribute to pipeline improvements, support deployments, troubleshoot routine issues, and take on smaller infrastructure tasks with guidance.

By 90 days: onboard 2–3 services to Kubernetes with appropriate pipelines, monitoring, and health checks, collaborating with senior engineers as needed.

Success includes reliable pipelines, smoother releases, successful Kubernetes operations, faster issue resolution, reduced manual work, better monitoring, and clear documentation.

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