Software Engineer

Red Hat
Raleigh$96k – $154kPosted 25 April 2026

Job Description

About the Job The Red Hat Performance and Scale Organization is seeking a software engineer to join our OpenShift Platform Performance and Scale Team. This role involves testing, measuring, and analyzing the performance and scalability of Red Hat OpenShift, the leading application modernization platform built on Kubernetes, to support the evolution of Red Hat OpenShift’s managed and layered offerings and to serve a wide variety of customer use cases. Red Hat OpenShift’s managed and layered offerings represent some of the most complex, customer-facing surfaces of the OpenShift ecosystem, spanning managed OpenShift services like ROSA, ARO, and OSD; layered products like enterprise container registry and image management through Quay or AI-assisted development via OpenShift Lightspeed; multi-cluster and hybrid cloud management through ACM; and the full Red Hat OpenShift AI platform, among others. Ensuring these products perform reliably at scale is critical to customer trust and Red Hat's ability to compete in an increasingly demanding market. This role will focus on performance and scalability testing across this portfolio, validating that each product meets the real-world demands of enterprise customers from initial deployment through production scale. The engineer will leverage their knowledge of distributed systems, cloud infrastructure, and layered platform architectures to theorize bottlenecks and limitations, devise test plans, execute workloads, collect and analyze data, and communicate findings. This role will require the ability to work cross-functionally with product management, engineering leadership, development teams, and quality engineers to measure performance, clearly articulate findings, and address bottlenecks. Time will also be spent collaborating with software engineering teams on bug fixes, code optimization, and resource usage reduction, as well as developing open-source tools for the reliability and repeatability of tests. This is a unique opportunity to work at the intersection of cutting-edge hardware and software! The broader mission of the Performance and Scale organization is to establish performance and scale leadership across the Red Hat product and cloud services portfolio. The scope includes component-level, system, and solution analysis and targeted enhancements. The team collaborates with engineering, product management, product marketing, customer support, and Red Hat’s hardware and software ecosystem partners. At Red Hat, our commitment to open source innovation extends beyond our products; it’s embedded in how we work and grow. Red Hatters embrace change – especially in our fast-moving technological landscape – and have a strong growth mindset. That's why we encourage our teams to proactively, thoughtfully, and ethically use AI to simplify their workflows, cut complexity, and boost efficiency. This empowers our associates to focus on higher-impact work, creating smart, more innovative solutions that solve our customers' most pressing challenges. What You Will Do Work closely with management, product owners, developers, and quality engineers to understand product requirements and build suitable test plans to verify the performance and scale of OpenShift Managed Services, Layered Products, AI Platforms, etc. Develop sophisticated tests that simulate user workloads through comprehensive end-to-end automation, leveraging custom-built and state-of-the-art open-source tools and frameworks. Deep dive into performance issues with the intent of discovering their root causes in complex distributed systems. Design and develop monitoring and reporting tools for performance and scale tests and analysis. Document your research and results clearly and concisely, and communicate findings both internally and externally. Engage in upstream communities to help test performance and scale early and influence design and development decisions. Triage, debug, and root cause customer issues related to Op ... (truncated, view full listing at source)
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