SDET, Portworx
SDET on Pure Storage's Portworx team in Bangalore, owning system-level quality for enterprise Kubernetes storage. Day to day: building Golang/Python automation suites, CI/CD test infrastructure, and driving HA, disaster-recovery, scale, and failure testing across Kubernetes, virtualization, and AI/ML workloads.
- Compensation
- Not disclosed
- Location
- Bangalore, India
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 8+ years
- Category
- Qa
- Posted
Skills
Must have
- 3+ years as an SDET, able to design complex distributed system test failure scenarios
- Strong Golang and/or Python programming skills (Golang preferred)
- Software testing/SDET experience, preferably with distributed systems, infrastructure, storage, or virtualization
- Strong debugging skills across Kubernetes, Linux, storage, and virtualization
- Strong hands-on experience with Kubernetes and Kubernetes application lifecycle management
- Strong background in enterprise storage (file/block/object) and Kubernetes persistent storage/CSI
- Experience developing and maintaining automation frameworks and CI/CD pipelines
- Ability to lead by example and take end-to-end ownership of product quality
- Ability to work on multiple concurrent product/feature releases
- Excellent communication and collaboration skills across geographically distributed teams
- Ability to mentor engineers and conduct automation/code reviews
Nice to have
- Experience with VMware/Hyper-V, KubeVirt, or Red Hat OpenShift Virtualization
- Experience with Kubernetes platforms such as OpenShift, EKS, AKS, or GKE
- Working experience with public clouds such as AWS, Azure, and Google Cloud
- Experience with tools such as Git, Jenkins/GitHub Actions, Jira, Confluence, and X-ray
Full description
Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem.
This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us.
SHOULD YOU ACCEPT THIS CHALLENGE...
We’re in an unbelievably exciting area of tech, fundamentally reshaping the cloud-native, modern virtualization, and AI infrastructure landscape. Here, you’ll lead with innovative thinking, grow alongside us, and work with some of the smartest minds in the industry.
We’re looking for engineers passionate about system testing, distributed systems, Kubernetes, storage, modern virtualization, AI workloads, and automation. You’ll work on complex, real-world scenarios involving HA, resiliency, disaster recovery, scalability, and failure testing across large-scale Kubernetes environments.
As enterprises modernize their infrastructure, containers, virtual machines, and AI/ML workloads are increasingly converging on Kubernetes. From traditional enterprise applications and VMs to GPU-accelerated AI training, inference, and data-intensive workloads, Kubernetes is rapidly becoming the common platform for running the next generation of applications.
This role gives you the opportunity to test and influence how Portworx delivers enterprise-grade storage, data protection, availability, and resiliency across these workloads—including containerized applications, KubeVirt/OpenShift Virtualization VMs, and demanding AI/ML workloads running on Kubernetes.
WHAT YOU WILL DO:
- Own system-level quality for Portworx Enterprise across Kubernetes, storage, and modern virtualization environments.
- Develop comprehensive test plans, test strategies, and automation for multiple concurrent product and feature releases.
- Build and maintain scalable automation test suites, with a strong focus on Golang-based automation and code quality.
- Drive validation of HA, resiliency, disaster recovery, upgrades, scale, and failure scenarios in large-scale Kubernetes environments.
- Identify functional and automation coverage gaps, assess risks early, and drive improvements to overall product quality.
- Collaborate with development, QE, and architecture teams across geographies to troubleshoot complex system-level issues and ensure timely releases.