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1 день назад

Site Reliability Engineer (AI)

Формат работы
remote
Тип работы
fulltime
Грейд
middle
Английский
b2
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR

Site Reliability Engineer (Kubernetes/AI): Managing and deploying containerized applications across GKE, EKS, and on-premises environments with an accent on high availability and infrastructure stability. Focus on improving monitoring stacks, implementing InfoSec configurations, and performing root-cause analysis to ensure seamless aircraft turnaround software operations.

Location: Remote

Company

hirify.global provides AI-based computer-vision software solutions to help global airports and airlines improve on-time performance, efficiency, and safety.

What you will do

  • Deploy and manage containerized applications across GKE, EKS, and on-premises Kubernetes environments.
  • Maintain complex infrastructure to ensure high availability and optimal performance via proactive administration.
  • Enhance and maintain monitoring and alerting stacks using Prometheus, Grafana, and Alertmanager.
  • Participate in on-call rotations and perform root-cause analysis (RCA) to resolve production issues.
  • Implement and manage InfoSec configurations, including firewall management and backup strategies.
  • Collaborate with Project Managers and cross-functional teams to align infrastructure with project requirements.

Requirements

  • 3+ years of experience as an SRE, IT Operations Engineer, or Systems Administrator.
  • Strong Linux system administration and deep understanding of networking concepts.
  • Hands-on experience managing Kubernetes clusters.
  • Proficiency with monitoring stacks including Prometheus, Grafana, and Alertmanager.
  • Automation mindset with scripting skills in Python, Bash, or similar.
  • Excellent verbal and written English skills.

Nice to have

  • Experience with on-premises Kubernetes installations, microservice architecture, and Helm.
  • Experience with Jsonnet for deployment configurations.
  • Understanding of Machine Learning, Computer Vision, or AI-based video analytics.
  • Familiarity with QA practices and CI/CD workflows.
  • Relevant certifications such as CKA/CKAD, AWS, or Google Cloud.

Culture & Benefits

  • Always remote work with a flexible schedule.
  • Paid vacation and sick leaves.
  • Budget for relevant courses and online education.
  • Company culture based on honesty and mutual respect.
  • Live team events.

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