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Kubernetes Technical Support Engineer

salary Salary :

$30,000 - 60,000 monthly

icon building Company : Axented
icon briefcase Job Type : Full Time
icon remote-alt Remote / Work from Home

Job Description - Kubernetes Technical Support Engineer

The project is an AI vision platform running on Kubernetes and used for enterprise video analytics. We are looking for a highly technical Tier 2 / Tier 3 Technical Support Engineer to help customers troubleshoot and resolve complex platform, infrastructure, and deployment issues.

Responsibilities

  • Provide Tier 2 / Tier 3 technical support to enterprise customers.
  • Troubleshoot Kubernetes-based deployments, software, infrastructure, hardware, networking, and configuration issues.
  • Reproduce customer environments and run tests to diagnose technical problems.
  • Work directly with customers during technical discussions and troubleshooting sessions.
  • Manage and resolve technical support tickets.
  • Collaborate with Engineering, Sales, and Customer Success teams.
  • Escalate complex issues and product bugs to Engineering and help drive them to resolution.
  • Clearly communicate technical findings, workarounds, and resolutions to customers.

Requirements

  • 2+ years of technical support experience, preferably in Tier 2 / Tier 3 support.
  • Strong hands-on Kubernetes experience in production environments.
  • At least one relevant Kubernetes or cloud certification, such as CKA, CKAD, CKS, AWS, Azure, or equivalent.
  • Strong troubleshooting skills across software, infrastructure, networking, and distributed environments.
  • Experience working directly with customers in a technical capacity.
  • Strong written and verbal English communication skills.
  • Ability to independently investigate complex technical issues and collaborate with engineering teams.

Nice to have

  • Experience with AWS, Azure, or other cloud platforms.
  • Linux troubleshooting experience.
  • Experience with containers, networking, monitoring, and logging.
  • Experience supporting enterprise software products.
  • Exposure to AI, computer vision, video analytics, or similar technologies
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