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2 дня назад

Cloud Platform Engineer (AI)

Формат работы
hybrid
Тип работы
fulltime
Грейд
middle
Английский
b2
Страна
US
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
Cloud Platform Engineer (AI): Operating and evolving a Kubernetes-based platform for AI workloads, including LLM gateways, agent runtimes, cloud model integrations, and infrastructure as code with an accent on multi-provider routing, observability, security, and GPU-based inference. Focus on designing reliable multi-tenant platform capabilities, implementing GitOps and monitoring workflows, and prototyping self-hosted model serving.

Location: Hybrid, with locations in Charlotte, North Carolina and New York, United States.

Company

hirify.global is a growing public company focused on creating better outcomes for its people and clients.

What you will do

  • Operate and evolve a Kubernetes-based platform for AI workloads, including LLM gateways, agent and tool-integration gateways, and agent runtimes.
  • Integrate and manage cloud-hosted foundation models across multiple providers, including routing, quotas, fallbacks, cost controls, and tenant isolation.
  • Deliver infrastructure as code and GitOps workflows.
  • Build monitoring, alerting, and tracing for AI workloads, and help design and prototype self-hosted model serving with GPU workloads and inference runtimes.
  • Harden the platform through secrets management, network policies, authentication and authorization, and audit logging.
  • Support internal product teams through documentation, onboarding, and troubleshooting.

Requirements

  • 3+ years of experience in platform, DevOps, SRE, or cloud engineering.
  • Hands-on Kubernetes experience, including deployments, networking, and troubleshooting.
  • Experience with infrastructure as code using Terraform and GitOps tooling such as Argo CD, Flux, or similar.
  • Solid experience with at least one major cloud provider: Azure or AWS.
  • Experience with observability tools such as OpenTelemetry, Prometheus, and Grafana.
  • Scripting and coding skills in Python, Go, or Bash, plus CI/CD experience.

Nice to have

  • Experience with LLM gateways or proxies, or LLM observability and tracing tools.
  • Familiarity with managed model services from major cloud providers such as Azure or AWS.
  • Understanding of agent frameworks and tool-integration protocols such as Model Context Protocol (MCP).
  • Experience running GPU workloads or model inference serving.
  • Experience in multi-tenant, regulated, or compliance-driven environments.

Culture & Benefits

  • Collaborative, open, and flexible work environment focused on creativity, innovation, teamwork, and professional growth.
  • Professional development opportunities, including reimbursement for training and continuing education.
  • Modern open offices with complimentary lunches and fully stocked kitchens.
  • Wellness programs, flexible time off, and family-formation benefits.
  • Paid volunteer time off and donation matching.

Hiring process

  • The hiring process generally includes three or more virtual or in-person meetings.

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