- Design and implement production infrastructure in AWS or Microsoft Azure within established architectural patterns
- Build and maintain Infrastructure as Code using Terraform, including reusable modules and environment separation
- Develop and improve CI/CD pipelines with automated validation, testing, security scanning, and rollback mechanisms
- Deploy and support containerized workloads using Docker, Kubernetes, and Helm
- Configure cloud networking, IAM/RBAC, workload identities, and secrets management
- Build observability solutions using metrics, logs, and traces
- Investigate and resolve production incidents across cloud platforms, Kubernetes, Linux systems, networking, and application runtime layers
- Conduct root-cause analysis and implement preventive remediation measures
- Review infrastructure and deployment changes prepared by peers
- Clarify technical and operational requirements and translate them into implementable infrastructure solutions
- Prepare technical documentation including architecture diagrams, runbooks, and recovery procedures
- Maintain accurate documentation and operational reporting aligned with production environments
- 2–5 years of hands-on experience supporting production systems and operational environments
- Strong practical experience with AWS or Microsoft Azure
- Strong Terraform expertise, including modules, state management, lifecycle configuration, and CI/CD integration
- Hands-on experience with Kubernetes and Helm
- Experience with CI/CD platforms such as GitHub Actions, GitLab CI/CD, Azure DevOps, or Jenkins
- Practical understanding of security best practices including IAM, secrets management, certificate handling, and container security
- Experience with observability and monitoring tools such as Prometheus, Grafana, OpenTelemetry, CloudWatch, Azure Monitor, ELK, or OpenSearch
- Strong Linux administration and networking knowledge including TCP/IP, DNS, routing, TLS, and performance analysis
- Shell scripting and automation experience
- Basic Python knowledge will be beneficial
- Ability to analyze requirements, identify risks and dependencies, and communicate technical decisions clearly
- Experience using AI-assisted engineering tools responsibly for research, troubleshooting, automation, and documentation
- Strong problem-solving and incident investigation skills
- Upper-Intermediate English level
WILL BE A PLUS
- Experience with both AWS and Microsoft Azure
- Experience defining and maintaining SLI/SLO practices
- Knowledge of OpenTelemetry-based observability implementations
- Experience with large-scale distributed production systems
- Python development or advanced scripting skills
- Experience mentoring junior engineers
- Exposure to platform architecture design and cloud governance practices