We are seeking a highly skilled and experienced Staff Cloud Operations Engineer
to join our growing Cloud Operations team. In this critical role, you will be
responsible for designing, implementing, and optimizing our comprehensive
monitoring and alerting strategy across our cloud infrastructure and
applications. You will drive proactive identification of issues, ensure system
health, and contribute significantly to our operational excellence and
reliability goals. We're looking for the best and the brightest 'A' players who
want to make a difference doing a job they love.
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Responsibilities
- Manage and maintain Extreme Cloud product and services
- Participate in developing the Edge Cloud Support System
- Troubleshoot and follow up on Cloud infrastructure / application related
issues
- Participate in continuous cloud service operations with US, EU, and China
teams.
- Communicate with Dev/QA as well as external carriers to resolve and prevent
issues.
- Improve and implement deployment automation platform for Kubernetes based
microservices.
- Improve service availability and scalability through tuning, automation,
tools, and process.
- Analyze service performance, identify bottleneck, and provide actionable
improvement plans.
- Provide 24* 7 support for Edge Cloud products and services
- Participate in cloud security and compliance implementation.
Ideal Qualifications
- BS level technical degree required; Computer Science or Engineering
background preferred.
- 5+ years of experience in a CloudOps / DevOps role.
- Hands-on experience with AWS or any public cloud (Azure, GCP etc).
- Hands-on experience with container-based architecture and deployment (Docker,
Kubernetes.)
- Hands-on experience with deployment automation development (ArgoCD,
Terraform, Helm).
- Experience in diagnosing and resolving complex application problems.
- Working Knowledge of Linux, security, and networking fundamentals.
- Working knowledge of Elasticsearch, PostgreSQL, Redis, Ignite, Kafka and
RabbitMQ.
- Comfortable working within a distributed team located in multiple time zones.
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