{"id":2634991,"url":"https://alion.io/job/qualys-site-reliability-engineer","title":"Site Reliability Engineer","company":{"id":18966,"name":"Qualys","domain":"qualys.com","url":"https://alion.io/company/qualys","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":null},"role":"DevOps","role_family":"DevOps","seniority":"junior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Raleigh, United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":63000,"max_usd":147000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":33},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon S3","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"Bash","optional":false},{"name":"CI/CD","optional":false},{"name":"Delta Lake","optional":false},{"name":"GCP","optional":false},{"name":"Grafana","optional":false},{"name":"Incident Management","optional":false},{"name":"Java","optional":false},{"name":"Kubernetes","optional":false},{"name":"Linux","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Prometheus","optional":false},{"name":"Python","optional":false},{"name":"Qualys Cloud Platform","optional":false},{"name":"Scala","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Unix","optional":false},{"name":"AppDynamics","optional":true},{"name":"Bitbucket","optional":true},{"name":"CloudFormation","optional":true},{"name":"GitHub","optional":true},{"name":"Jenkins","optional":true},{"name":"Splunk","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-10-14T00:00:00Z","employer_posted_date":"2026-10-14","last_verified_at":"2026-10-15T21:53:39Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Come work at a place where innovation and teamwork come together to support the most exciting missions in the world!\nSite Reliability Engineer (SRE)\nThe Opportunity\nThe 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.\nThe 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.\nWhere This Role Sits\nThe SRE role partners closely with Engineering, DevOps, Infrastructure, Security, and Data Platform teams to ensure production systems remain resilient, scalable, observable, and operationally efficient.\nThe 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.\nKey Responsibilities\nReliability and Operations\nMonitor production applications, infrastructure, and distributed systems to identify issues and maintain service health.\nParticipate in incident response, troubleshooting, escalation, and root-cause analysis.\nSupport highly available and scalable production services and workloads.\nMonitor system performance, resource utilization, availability, latency, and overall service health.\nParticipate in on-call rotations and follow established incident management processes.\nSupport capacity planning and identify potential reliability and performance risks.\nAssist engineering teams in resolving production issues and implementing corrective actions.\nContribute to post-incident reviews and continuous reliability improvements.\nData Platform and Distributed Systems\nSupport the operation and monitoring of Apache Spark workloads and Kafka pipelines.\nMonitor distributed data-processing workloads and investigate performance or availability issues.\nAssist with troubleshooting Spark jobs, Kafka pipelines, application failures, resource constraints, and related production issues.\nDevelop an understanding of distributed systems concepts and their operational requirements.\nSupport data platforms and technologies such as Delta Lake and S3 where applicable.\nApply basic SQL skills for troubleshooting, validation, and operational analysis.\nKubernetes and Cloud Operations\nAssist with Kubernetes deployments, resource monitoring, application troubleshooting, and operational support.\nMonitor containerized applications and investigate resource, availability, and performance issues.\nSupport cloud environments such as AWS, OCI, or Google Cloud Platform.\nWork with infrastructure and engineering teams on configuration, deployments, and operational workflows.\nDevelop familiarity with Infrastructure as Code (IaC) and cloud-native operational practices.\nMonitoring and Observability\nMonitor applications, infrastructure, and distributed workloads using tools such as Prometheus and Grafana.\nCreate and maintain dashboards, alerts, and monitoring configurations.\nAnalyze logs, metrics, and system behavior to identify and troubleshoot production issues.\nTrack reliability indicators such as availability, latency, performance, resource utilization, and service health.\nContribute to improvements in observability and proactive issue detection.\nAutomation and Platform Engineering\nDevelop scripts and automation to reduce repetitive manual operational tasks.\nCreate tooling for monitoring, log analysis, troubleshooting, deployments, and operational workflows.\nUse Python, Bash, Go, or similar programming/scripting languages to automate operational processes.\nSupport CI/CD and automated deployment workflows.\nContribute to Infrastructure as Code and self-service capabilities where applicable.\nContinuously improve operational processes through automation and standardization.\nCollaboration and Continuous Improvement\nCollaborate with Engineering, DevOps, Infrastructure, Security, and Data Platform teams to improve system reliability.\nAssist development teams in designing and operating production-ready services.\nDocument system architectures, operational procedures, troubleshooting steps, and best practices.\nCreate and maintain runbooks, SOPs, and troubleshooting guides.\nProactively identify reliability risks and opportunities for operational improvement.\nContribute to SRE best practices, knowledge sharing, and continuous improvement initiatives.\nWhat Good Looks Like\nProactively identifies reliability and performance risks before they significantly impact customers.\nResponds effectively to production incidents and contributes to meaningful root-cause analysis.\nUses automation to reduce repetitive manual operational work.\nDemonstrates strong troubleshooting skills across Linux, Kubernetes, cloud, and distributed systems.\nEffectively monitors and analyzes system metrics, logs, and application behavior.\nCollaborates effectively with engineering and infrastructure teams to resolve production issues.\nContinuously improves system reliability, observability, scalability, and operational efficiency.\nBuilds a strong understanding of production systems and applies SRE principles to day-to-day operations.\nDistinguishing Expectations\nThe SRE is measured by improvements in reliability, automation, operational efficiency, observability, and service availability.\nFor an early-career SRE, success is demonstrated through:\nEffective monitoring and troubleshooting of production systems.\nRapid learning of complex production environments.\nReduction of manual operational effort through automation.\nConsistent participation in incident response and root-cause analysis.\nImprovements to monitoring, documentation, and operational processes.\nGrowing ownership of production services and reliability-focused initiatives.\nRequired Qualifications\n0-3 years of experience in SRE, DevOps, Cloud Engineering, Systems Engineering, or a related technical role.\nBachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.\nBasic understanding of Linux/Unix systems, processes, memory, networking, and system troubleshooting.\nFundamental understanding of distributed systems and cloud-native technologies.\nExperience or familiarity with Kubernetes and containerized applications.\nFamiliarity with Apache Spark, Kafka, or similar distributed data-processing platforms.\nStrong programming and scripting fundamentals in Python, Bash, Go, Java, Scala, or similar languages.\nAbility to write scripts for automation, monitoring, log analysis, and operational tasks.\nBasic SQL knowledge and strong problem-solving skills.\nFamiliarity with monitoring and observability tools such as Prometheus and Grafana.\nBasic understanding of cloud platforms such as AWS, OCI, or Google Cloud Platform.\nUnderstanding of basic networking, security, and distributed systems concepts.\nWillingness to learn production systems, debugging techniques, and SRE practices.\nPreferred Qualifications\nFamiliarity with Delta Lake, S3, or distributed data platforms.\nUnderstanding of CI/CD and automated deployment processes.\nFamiliarity with Terraform, CloudFormation, or other Infrastructure as Code tools.\nExperience with scripting-based automation or internal tooling projects.\nFamiliarity with tools such as Jenkins, GitHub, Bitbucket, ELK, Splunk, or AppDynamics.\nExperience with large-scale or distributed systems.\nUnderstanding of reliability engineering principles and automation best practices.\nExposure to incident management, on-call processes, and postmortem practices.\nCloud certifications are a plus.\nStrong analytical, communication, collaboration, and troubleshooting skills.\nCore Competencies\nSRE | Linux | Python / Bash / Go | Coding & Scripting | Spark | Kafka | Kubernetes | Cloud Platforms | SQL | Monitoring & Observability | Automation | Distributed Systems | Troubleshooting | Incident Response | CI/CD | Reliability Engineering\nWork Environment\nFull-time role.\nOn-call participation may be required.\nHybrid or remote flexibility depending on company policy.\nCross-functional collaboration with Engineering, DevOps, Infrastructure, Security, and Data Platform teams.\nOpportunity to work with cloud-native, distributed, and large-scale production systems.\nABOUT QUALYS\nQualys, Inc. is a pioneer and leading provider of cloud-based IT, security, and compliance solutions, serving more than 10,000 customers across over 130 countries. 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