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6 часов назад

DevOps Engineer (AI)

Формат работы
remote (Global)
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

Текст:
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TL;DR
DevOps Engineer (AI): Creating and evaluating production-style infrastructure and automation tasks for next-generation AI systems with an accent on CI/CD, Kubernetes, infrastructure as code, and cloud environments. Focus on building reproducible reference solutions, reviewing AI-generated workflows, and solving reliability, monitoring, and incident-response challenges.

Location: Remote

Company

hirify.global delivers consulting services focused on software engineering and AI-related infrastructure work.

What you will do

  • Design realistic DevOps tasks covering CI/CD, containers, Kubernetes, infrastructure as code, monitoring, and incident response.
  • Create working reference solutions with clear setup and validation steps.
  • Review AI-generated solutions, identify failures, and provide precise technical corrections.
  • Maintain correctness, reliability, and reproducibility across infrastructure workflows.
  • Provide structured feedback to improve AI-generated DevOps workflows.

Requirements

  • 3+ years of professional experience in DevOps, SRE, platform, or infrastructure engineering.
  • Hands-on experience with Docker, Kubernetes, CI/CD tools, and at least one major cloud platform.
  • Infrastructure as code experience with Terraform, Ansible, Pulumi, or CloudFormation.
  • Strong coding skills in Python, Go, Bash, or TypeScript.
  • Advanced Linux and Git skills.
  • Strong written and spoken English; availability for at least 20 hours per week.

Nice to have

  • Experience with Prometheus, Grafana, Datadog, or OpenTelemetry.
  • Background in security, secrets management, or platform reliability.
  • Open-source contributions or technical writing experience.
  • Experience with AI training data or model evaluation.

Culture & Benefits

  • Remote contractor engagement.
  • Work focused on production-style infrastructure and automation for next-generation AI systems.
  • Opportunities to apply DevOps engineering judgment to evaluate and improve AI-generated workflows.

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