This person will bring deep hands-on experience with Zabbix and a strong track record of using automation and AI tools to improve operational efficiency.
5+ years of experience working with enterprise-scale Zabbix environments.
Strong experience with automation and scripting, especially in Python.
Hands-on experience integrating AI or LLM tools into operational or infrastructure workflows.
Knowledge of data privacy and sanitization practices when sending operational data to external services.
Strong networking fundamentals, including protocols such as SNMP, Syslog, NetFlow, gRPC, and SSH.
Preferred: Zabbix certification and experience in large-scale infrastructure operations.

We are looking for an engineer to lead and improve our network monitoring environment. The role focuses on making monitoring smarter and more proactive by reducing alert noise, improving root-cause identification, and helping operations teams respond faster and more effectively. Own and improve the Zabbix monitoring platform across a mid, distributed environment. Build AI-assisted operational workflows that connect monitoring data with tools such as Anthropic Claude. Reduce alert fatigue by improving event correlation and filtering duplicate or downstream alerts. Support faster trouble-shooting by helping automate root-cause analysis and recommended next steps. Create automation toolsin Python, Bash, or Ansible to streamline monitoring and response workflows. Develop dashboards and reporting for both technical teams and leadership stakeholders. Produce executive-level SLO reporting that clearly communicates service health and performance.