DevOps Infrastructure Team Lead

Lead
Companynsogroup.com
LocationIsrael
CategoryInfrastructure
DepartmentResearch & Development
SeniorityLead
Workplace-
Posted2026-09-16
Estimated salary₪40K–55K (a market estimate, not the employer's figure)
Viawpjobs

Description

As a DevOps Infrastructure Team Lead,  you will :

  • Lead, mentor and grow a team of DevOps and Infrastructure engineers, providing technical direction and fostering ownership and continuous improvement
  • Own the core architecture, development and operation of the dev and production infrastructure and self-hosted AI environments, including on-premises GPU infrastructure
  • Lead Kubernetes-based infrastructure end to end, including system design, development, deployment, operations, troubleshooting and lifecycle management
  • Define infrastructure platform standards, best practices and engineering methodologies
  • Own the DevOps toolchain, including DevOps tools and monitoring\logging platforms
  • Partner closely with engineering teams to enable delivery and solve complex platform and infrastructure challenges
  • Evaluate and introduce new technologies through POCs and technical assessments
  • Drive incident resolution, root-cause analysis and continuous improvement of platforms and infrastructure services

If you have :

  • At least 5 years of hands-on experience in DevOps engineering
  • At least 2 years of experience in managing, leading or mentoring engineers
  • Proven ability to design, manage and maintain highly scalable production systems
  • Hands-on production experience with Kubernetes, including deployment, operations, troubleshooting and platform management
  • Strong experience with Terraform, Ansible and Helm
  • Prometheus, Grafana, and ELK or similar monitoring, observability and logging stacks
  • Strong programming/scripting skills in Python, Go, Ruby, Java, PowerShell or Bash
  • Experience with GitOps practices and tools such as Argo CD
  • Strong technical leadership, problem-solving and communication skills
  • A proactive, independent and hands-on approach, with a passion for learning and tackling complex challenges

It would be great if you also have :

  • Experience managing on-prem GPU infrastructure for AI/ML environments
  • Strong knowledge of networking fundamentals
  • Experience defining technical strategy, architecture and infrastructure roadmaps
  • Experience with highly available, large-scale or security-sensitive environments