Team Leader guiding Remote’s global SRE platform for compliant international employment. Leading engineers and reliability across Kubernetes, AWS, observability, and infrastructure.
About the role
- DevOps Engineer managing AWS, Kubernetes, CI/CD, and observability for StellarTech’s scalable global EdTech products. Improving reliability, security, and production operations across multiple products.
Responsibilities
- Design, implement, and maintain scalable cloud infrastructure
- Establish and manage CI/CD pipelines for reliable software deployment
- Manage Kubernetes services and troubleshoot cluster failures
- Optimise performance across distributed systems
- Handle production incidents and conduct post-mortems
- Identify root causes and improve reliability processes
- Implement and improve logging, monitoring, tracing, and alerting
- Monitor infrastructure resource usage and optimise cloud efficiency
- Manage global CDN configurations
- Maintain SSO systems, databases, backups, and recovery processes
- Support development, staging, and production environments
- Automate infrastructure and operational processes using scripts and Infrastructure as Code
- Collaborate with Backend, Product, and Engineering teams across multiple products
Requirements
- Strong hands-on experience with AWS and cloud architecture and operations
- Strong knowledge of Kubernetes and Docker, including production-grade cluster management
- Experience with managed Kubernetes platforms such as EKS, GKE, or AKS
- Advanced experience with Terraform, Helm, and Git
- Hands-on experience implementing and maintaining GitHub Actions for CI/CD pipelines
- Experience with Prometheus, Grafana, and OpenTelemetry
- Ability to automate system and deployment tasks using Python and Bash
- Strong troubleshooting skills and experience with distributed production systems
- Experience using AI-assisted development tools such as Claude, Cursor, GitHub Copilot, ChatGPT, Codex, or similar
- Hands-on experience managing API gateways for high-traffic applications
- Experience with machine learning projects, including deploying, monitoring, and scaling ML workloads
- Familiarity with machine learning platforms, frameworks, or libraries
- Experience in a DBA role, including managing, maintaining, and optimising large-scale databases
Benefits
- Company-provided medical expense compensation
- AI subscription and other tools
- Flexible paid time off
- 21 days of annual leave
- 10 bank holidays
- Global remote work
- Collaborative culture
Job title
Job type
Experience level
Salary
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Degree requirement
No Education Requirement
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