Site Reliability Engineer, Cloud Platform

Come work at a place where innovation and teamwork come together to support the most exciting missions in the world! Site Reliability Engineer (SRE) The Opportunity The Site Reliability Engineer (SRE) plays a critical role in ensuring the reliability, scalability, performance, and operational excellence of Qualys platforms and services. This role operates at the intersection of software engineering and operations, applying automation, observability, troubleshooting, and reliability engineering practices to maintain highly available production systems and improve customer experience. The SRE will work closely with Engineering, DevOps, Infrastructure, Security, and Data Platform teams to monitor production systems, troubleshoot issues, automate operational processes, and continuously improve system reliability. Where This Role Sits The SRE role partners closely with Engineering, DevOps, Infrastructure, Security, and Data Platform teams to ensure production systems remain resilient, scalable, observable, and operationally efficient. The role provides hands-on support for cloud-native and distributed systems, including Kubernetes, Apache Spark, Kafka, and cloud-based data platforms , while contributing to incident response, automation, monitoring, and reliability improvements.

Reliability and Operations Monitor production applications, infrastructure, and distributed systems to identify issues and maintain service health. Participate in incident response, troubleshooting, escalation, and root-cause analysis. Support highly available and scalable production services and workloads. Monitor system performance, resource utilization, availability, latency, and overall service health. Participate in on-call rotations and follow established incident management processes. Support capacity planning and identify potential reliability and performance risks. Assist engineering teams in resolving production issues and implementing corrective actions. Contribute to post-incident reviews and continuous reliability improvements. Data Platform and Distributed Systems Support the operation and monitoring of Apache Spark workloads and Kafka pipelines . Monitor distributed data-processing workloads and investigate performance or availability issues. Assist with troubleshooting Spark jobs, Kafka pipelines, application failures, resource constraints, and related production issues. Develop an understanding of distributed systems concepts and their operational requirements. Support data platforms and technologies such as Delta Lake and S3 where applicable. Apply basic SQL skills for troubleshooting, validation, and operational analysis. Kubernetes and Cloud Operations Assist with Kubernetes deployments, resource monitoring, application troubleshooting, and operational support . Monitor containerized applications and investigate resource, availability, and performance issues. Support cloud environments such as AWS, OCI, or Google Cloud Platform . Work with infrastructure and engineering teams on configuration, deployments, and operational workflows. Develop familiarity with Infrastructure as Code (IaC) and cloud-native operational practices. Monitoring and Observability Monitor applications, infrastructure, and distributed workloads using tools such as Prometheus and Grafana . Create and maintain dashboards, alerts, and monitoring configurations. Analyze logs, metrics, and system behavior to identify and troubleshoot production issues. Track reliability indicators such as availability, latency, performance, resource utilization, and service health. Contribute to improvements in observability and proactive issue detection. Automation and Platform Engineering Develop scripts and automation to reduce repetitive manual operational tasks. Create tooling for monitoring, log analysis, troubleshooting, deployments, and operational workflows. Use Python, Bash, Go, or similar programming/scripting languages to automate operational processes.