Site Reliability Engineer, Cloud Platform

Overview

Site Reliability Engineer on Qualys' Cloud Platform team, ensuring the reliability, scalability, performance and operational excellence of Qualys platforms and services by combining software engineering with operations practices.

What you'll do

• 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.
• 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.
• 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.
• 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.
• 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.
• Support CI/CD and automated deployment workflows.
• Contribute to Infrastructure as Code and self-service capabilities where applicable.
• Continuously improve operational processes through automation and standardization.
• Collaborate with Engineering, DevOps, Infrastructure, Security and Data Platform teams to improve system reliability.
• Assist development teams in designing and operating production-ready services.
• Document system architectures, operational procedures, troubleshooting steps and best practices.
• Create and maintain runbooks, SOPs and troubleshooting guides.
• Proactively identify reliability risks and opportunities for operational improvement.
• Contribute to SRE best practices, knowledge sharing and continuous improvement initiatives.

What you'll need

• 0–3 years of experience in SRE, DevOps, Cloud Engineering, Systems Engineering or a related technical role.
• Bachelor's degree in Computer Science, Engineering or a related field, or equivalent practical experience.
• Basic understanding of Linux/Unix systems, processes, memory, networking and system troubleshooting.
• Fundamental understanding of distributed systems and cloud-native technologies.
• Experience or familiarity with Kubernetes and containerized applications.
• Familiarity with Apache Spark, Kafka or similar distributed data-processing platforms.
• Strong programming and scripting fundamentals in Python, Bash, Go, Java, Scala or similar languages.
• Ability to write scripts for automation, monitoring, log analysis and operational tasks.
• Basic SQL knowledge and strong problem-solving skills.
• Familiarity with monitoring and observability tools such as Prometheus and Grafana.
• Basic understanding of cloud platforms such as AWS, OCI or Google Cloud Platform.
• Understanding of basic networking, security and distributed systems concepts.
• Willingness to learn production systems, debugging techniques and SRE practices.

Nice to have

• Familiarity with Delta Lake, S3 or distributed data platforms.
• Understanding of CI/CD and automated deployment processes.
• Familiarity with Terraform, CloudFormation or other Infrastructure as Code tools.
• Experience with scripting-based automation or internal tooling projects.
• Familiarity with tools such as Jenkins, GitHub, Bitbucket, ELK, Splunk or AppDynamics.
• Experience with large-scale or distributed systems.
• Understanding of reliability engineering principles and automation best practices.
• Exposure to incident management, on-call processes and postmortem practices.
• Cloud certifications.
• Strong analytical, communication, collaboration and troubleshooting skills.

Details

• Full-time role in Pune.
• On-call participation may be required.
• Hybrid or remote flexibility depending on company policy.