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2 дня назад

Staff Infrastructure Engineer (Cloud)

171 000 - 225 000CAD
Формат работы
remote (только Canada)/hybrid
Тип работы
fulltime
Грейд
lead
Английский
b2
Страна
Canada
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR

Staff Infrastructure Engineer (Cloud): Designing and implementing complex, cross-team infrastructure systems for a global streaming platform with an accent on scalability, reliability, and developer velocity. Focus on building production-grade infrastructure software, evolving video delivery architectures, and partnering with AI/ML teams to define GPU-powered workflows.

Location: Must be based in Canada (Waterloo, Toronto, or Vancouver areas are preferred for hybrid collaboration)

Salary: $171,000–$225,000 CAD

Company

hirify.global is a streaming platform providing unprecedented access to classes from world-renowned instructors across diverse fields.

What you will do

  • Set technical direction for core cloud infrastructure systems and shared platforms.
  • Design and lead cross-team initiatives using AWS, Kubernetes, and Infrastructure as Code.
  • Build automation tools and internal platforms to enhance developer velocity.
  • Collaborate with AI and Data teams to define and scale GPU-powered infrastructure and inference workflows.
  • Lead initiatives to evolve video delivery and CDN strategies for global scale.
  • Act as a technical leader and mentor, driving operational excellence and architectural consistency.

Requirements

  • 10+ years of experience building and operating cloud-native production systems.
  • Expertise in AWS architecture and large-scale cloud operations.
  • Advanced knowledge of Kubernetes (EKS), including networking, RBAC, and autoscaling.
  • Proficiency in Infrastructure as Code using Terraform.
  • Strong background in distributed systems, Linux internals, and cloud security.
  • Excellent written and verbal communication skills to influence technical decisions across the organization.

Nice to have

  • Experience with AI/ML infrastructure, GPU scheduling, or distributed model training frameworks.
  • Knowledge of service mesh, KEDA, Karpenter, or multi-cluster architectures.
  • Familiarity with HLS/DASH video packaging and encoding pipelines.

Culture & Benefits

  • Remote-first workforce with collaborative office spaces.
  • Commitment to diversity, inclusion, and equal opportunity employment.
  • Focus on craftsmanship, long-term maintainability, and pragmatic problem-solving.
  • Environment that prioritizes technical leadership and strategic ownership.

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