Performance Tester / Platform Engineer

Type of Requisition:RegularClearance Level Must Currently Possess:NoneClearance Level Must Be Able to Obtain:NonePublic Trust/Other Required:BI Full 6C (T4)Job Family:Professional EngineeringJob Qualifications:Skills:Performance Testing, Performance Testing Strategy, Performance Testing ToolsCertifications:NoneExperience:5 + years of related experienceUS Citizenship Required:NoJob Description:Transform technology into opportunity as a Performance Tester / Platform Engineer at GDIT. Shape what’s next for mission-critical government projects while shaping what’s next for your engineering career. The Case Management Modernization (CMM) Program is an initiative to support the Administrative Office (AO) of the US Courts (AO) develop a modern cloud-based solution to support all 204+ federal courts across the United States which are grouped into three types, namely Appellate, District, and Bankruptcy. This modernized case management system will eventually replace the current Case Management and Electronic Case Filing (CM/ECF) system. The Performance Tester / Platform Engineer will work as part of an agile development team to build and support the modernization of enterprise-class software applications. MEANINGFUL WORK AND PERSONAL IMPACT As a Performance Tester / Platform Engineer, the work you’ll do at GDIT will be impactful to the mission of US Courts. You will play a crucial role in the following areas: Design, implement, and maintain automated performance testing frameworks integrated into CI/CD pipelines for cloud-native applications Define and track key performance KPIs (e.g., response time, throughput, resource utilization, latency, error rates) based on SLAs and stakeholder requirements Conduct load, stress, and scalability testing to validate performance under multi-tenant conditions and concurrent user loads Develop and manage a performance dashboard and provide executive-level and technical-level reporting on system behavior Perform real-time monitoring, observability, and telemetry setup for application and infrastructure performance using modern tools and dashboards Collaborate with developers, QA, SREs, and operations teams to identify performance bottlenecks and provide optimization recommendations Validate the performance of critical workflows and use cases, including long-running queries, search operations, and API endpoints Capture and report on system metrics such as CPU, memory, disk, network, and application-specific logs for tuning and diagnostics Contribute to the performance section of the Monthly Status Report (MSR) and sprint-level performance documentation Ensure alignment of performance testing strategy with DevSecOps and MLOps processes for continuous integration and delivery Developing and executing formal performance test plans to ensure the delivery of quality software applications Composing and maintaining comprehensive test plans and reports Verifying and validating functionality by evaluating software against system requirements Responsible for supporting cloud solution resources, both IaaS and PaaS, that enable the business to securely run sensitive workloads within a cloud Implementing and designing server, network, and software configurations for a cloud computing infrastructure and applications with a focus on DevOps principles WHAT YOU’LL NEED TO SUCCEED Bring your engineering expertise along with a drive for innovation to GDIT. The Performance Tester / Platform Engineer must have:● Education: Bachelor of Science● Experience: 5+ years of related experience; 1+ year should involve deploying and managing applications and systems to commercial and private clouds● Required Skills: Experience in performance engineering and automated testing of cloud-based applications and platforms Strong knowledge of performance testing tools such as JMeter, Gatling, LoadRunner, BlazeMeter, or k6 Hands-on experience with CI/CD pipelines using tools such as Jenkins, GitLab CI, Azure DevOps, or GitHub Actions Experience with monitoring and observability tools such as Grafana, Prometheus, Datadog, New Relic, CloudWatch, or Elastic Stack Proficiency in scripting languages such as Python, Bash, or JavaScript for automation of testing and reporting workflows Familiarity with containerized environments (Docker, Kubernetes) and microservices testing strategies Strong understanding of cloud infrastructure performance characteristics, especially AWS, Azure, or GCP Experience with telemetry frameworks and logging standards to support traceability and root cause analysis Demonstrated ability to analyze large volumes of test data, identify trends, and drive root cause identification and tuning Experience working in Agile/Scrum teams and participating in sprint ceremonies Experienced in providing DevSecOps implementation using GitOps, or similar tools Experienced in developing, testing, and maintaining containerized applications utilizing docker, k8s, Openshift, etc. Working knowledge of Source Version Cont