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5 дней назад

Senior Platform Engineer (GCP)

Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
Israel
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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TL;DR

Senior Platform Engineer (GCP/Kubernetes): Building a high-velocity, self-service internal infrastructure product with an accent on architectural modularization and Kubernetes-native abstractions. Focus on designing controllers and operators, implementing everything-as-code, and ensuring production reliability via robust observability.

Location: Tel Aviv, Israel

Company

hirify.global leverages cutting-edge AI and Large Market Models (LMM) to revolutionize demand forecasting and real-time decision-making, starting with the airline industry.

What you will do

  • Build secure, automated self-service pathways to accelerate development while maintaining organizational standards.
  • Design Kubernetes-native abstractions, including controllers and operators, to decouple infrastructure into independent service lifecycles.
  • Implement an Everything-as-Code discipline for infrastructure, policy, and configuration using a full SDLC (versioning, reviews, tests, CI).
  • Ensure production reliability through robust observability, clear SLOs, and leading blameless postmortems.

Requirements

  • Strong production-scale experience with GCP (GKE, IAM, networking, Cloud SQL/BigQuery).
  • Deep Kubernetes-native mindset with expertise in declarative-first design, controllers, and operators.
  • Proficiency with Terraform, Helm, and GitOps tools (e.g., ArgoCD).
  • Software engineering background with strong production coding ability in Go and/or Python.
  • Strong security awareness, including least-privilege IAM and secret hygiene.
  • Production-first mindset with a focus on reliability, observability, and recoverability.

Nice to have

  • Experience with Policy-as-code (OPA/Conftest, Kyverno) and CI security tooling.
  • Practice with SLO/error-budgets and DORA-based delivery measurement.
  • Multicloud experience with AWS or Azure.
  • Exposure to Big Data or MLOps tools such as Airflow, Dagster, Ray, or Kubeflow.
  • Perspectives on AI-assisted and spec-driven development.

Culture & Benefits

  • Opportunity to work in a rapidly scaling environment.
  • Focus on developer independence and high-velocity delivery.
  • Culture of operational hygiene and system reliability.

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