8 дней назад
DevOps Engineer (Kubernetes)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
DevOps Engineer (Kubernetes/AWS): Building and operating scalable cloud infrastructure, Kubernetes environments, CI/CD pipelines, and observability systems for global EdTech products with an accent on reliability, security, and cloud efficiency. Focus on troubleshooting distributed production systems, automating infrastructure with Terraform and Python, managing incidents, and supporting AI and machine learning workloads.
Location: Global remote
Company
is a multi-product IT company building scalable EdTech products for global markets, including AI-driven products.
What you will do
- Design, implement, and maintain scalable AWS cloud infrastructure across multiple products.
- Manage production-grade Kubernetes clusters, Docker-based services, and CI/CD pipelines.
- Improve system reliability through observability, monitoring, logging, tracing, alerting, and performance optimization.
- Handle production incidents, conduct post-mortems, identify root causes, and improve reliability processes.
- Manage CDN configurations, SSO systems, databases, backups, recovery processes, and development, staging, and production environments.
- Automate infrastructure and operational processes using Terraform, Helm, Python, Bash, and Infrastructure as Code.
Requirements
- Strong hands-on experience with AWS, cloud architecture, and cloud operations.
- Strong knowledge of Kubernetes and Docker, including production-grade cluster management and experience with 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, OpenTelemetry, distributed production systems, and troubleshooting.
- Ability to automate system and deployment tasks with Python and Bash, plus experience using AI-assisted development tools.
Nice to have
- Experience managing API gateways for high-traffic applications.
- Experience deploying, monitoring, and scaling machine learning workloads.
- Familiarity with machine learning platforms, frameworks, or libraries.
- Experience in a DBA role managing and optimizing large-scale databases.
Culture & Benefits
- Global remote work environment.
- Company-provided medical expense compensation.
- AI subscriptions and other tools.
- Flexible paid time off, including 21 days of annual leave and 10 bank holidays.
- Collaborative environment focused on innovation in EdTech.
Hiring process
- HR interview.
- Technical interview.
- Final interview.
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