CloudOps Engineer (Automation Specialist
Role details
Job location
Tech stack
Job description
The CloudOps Engineer (Automation) is responsible for the design, deployment, and operational management of our cloud infrastructure. Unlike traditional operations roles, this position prioritizes automation-first methodologies. You will eliminate manual toil by building scalable, self-healing systems and robust CI/CD pipelines to support rapid software delivery., * Infrastructure as Code (IaC): Architect and maintain multi-tier infrastructure using Terraform, CloudFormation, or Bicep.
- CI/CD Management: Design and optimize automated deployment pipelines (GitHub Actions, GitLab CI, or Jenkins) to ensure "zero-touch" deployments.
- Configuration Management: Utilize tools like Ansible or Chef to manage OS-level configurations and application state., * Container Orchestration: Manage and scale production workloads using Kubernetes (EKS/AKS/GKE) and Docker.
- Performance Tuning: Monitor system performance and automate scaling policies to handle fluctuating traffic patterns.
- Cost Governance: Implement automated reporting and resource scheduling to optimize cloud spend., * Observability: Build comprehensive dashboards and alerting systems using Datadog, Prometheus, or Grafana.
- Incident Response: Participate in on-call rotations and lead "Post-Mortem" analyses to turn manual fixes into automated remediations.
- DevSecOps: Integrate automated security scanning (SAST/DAST) and IAM guardrails into the infrastructure lifecycle.
Requirements
Cloud Platforms
3+ years of experience with AWS, Azure, or Google Cloud Platform.
Scripting
Proficiency in Python, Go, or advanced Bash scripting.
IaC
Expert-level experience with Terraform and Git workflows.
Containers
Strong understanding of Kubernetes (Ingress, ConfigMaps, Helm).
Networking
Deep knowledge of VPCs, DNS, Load Balancers, and VPNs.
Preferred Mindset
- Efficiency Obsessed: You seek to automate any task that must be performed more than once.
- Collaborative: You act as a bridge between Development and Operations teams.
- Analytical: You use data and logs to drive infrastructure decisions rather than "gut feelings."