Senior Site Reliability Engineer

Build products with MVRs and reliability standards , ensuring system resilience and scalability. Set up and operate observability tools across multiple cloud providers, incorporating AI-powered anomaly detection to enhance monitoring. Assist development teams in defining SLO/SLI dashboards and alerts , optimizing alerting signals with ML-based noise reduction techniques . Use Go, Python, or Terraform to automate operational tasks and build self-healing mechanisms. Manage and administer Grafana, Prometheus, Loki, and other observability tools , integrating predictive analytics where beneficial. Troubleshoot and support production environments , using AI-assisted diagnostics where applicable for faster root cause identification. Automate incident response workflows, leveraging AIOps to reduce manual toil and improve MTTR. What Youll Need to be Successful Minimum of 5 years experience in a SaaS environment . Bachelors degree or equivalent experience. Ability to participate in an on-call rotation . Strong understanding of networking (OSI model, TCP/IP, DNS), particularly in cloud environments . Experience with Linux administration, security hardening, and performance tuning . Passion for troubleshooting distributed systems and software failures. Deep understanding of observability principles , including log analysis, tracing, and metrics correlation . Strong background in infrastructure as code (Terraform, Pulumi) and container orchestration (Kubernetes, ECS, Nomad) . Interest in AI-powered automation , including AIOps tools, ML-based alert tuning, and predictive maintenance . Experience with Observability tools like Prometheus,grafana or OpenTelemetry with ML-based anomaly detection is a plus. Excellent technical writing skills for documenting architectures, processes, and automation workflows Build products with MVRs and reliability standards , ensuring system resilience and scalability. Set up and operate observability tools across multiple cloud providers, incorporating AI-powered anomaly detection to enhance monitoring. Assist development teams in defining SLO/SLI dashboards and alerts , optimizing alerting signals with ML-based noise reduction techniques . Use Go, Python, or Terraform to automate operational tasks and build self-healing mechanisms. Manage and administer Grafana, Prometheus, Loki, and other observability tools , integrating predictive analytics where beneficial. Troubleshoot and support production environments , using AI-assisted diagnostics where applicable for faster root cause identification. Automate incident response workflows, leveraging AIOps to reduce manual toil and improve MTTR. What Youll Need to be Successful Minimum of 5 years experience in a SaaS environment . Bachelors degree or equivalent experience. Ability to participate in an on-call rotation . Strong understanding of networking (OSI model, TCP/IP, DNS), particularly in cloud environments . Experience with Linux administration, security hardening, and performance tuning . Passion for troubleshooting distributed systems and software failures. Deep understanding of observability principles , including log analysis, tracing, and metrics correlation . Strong background in infrastructure as code (Terraform, Pulumi) and container orchestration (Kubernetes, ECS, Nomad) . Interest in AI-powered automation , including AIOps tools, ML-based alert tuning, and predictive maintenance . Experience with Observability tools like Prometheus,grafana or OpenTelemetry with ML-based anomaly detection is a plus. Excellent technical writing skills for documenting architectures, processes, and automation workflows