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. We're in an unbelievably exciting area of tech, fundamentally reshaping the cloud-native, modern virtualization, and AI infrastructure landscape. 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.

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 solid 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 .

Ensure CI/CD pipelines and automation infrastructure effectively execute the required functional, regression and system test strategies.

Strong SDET mindset — engineering for quality and ability to design complex distributed system test failure scenarios

Ability to lead by example and take end-to-end ownership of product quality .

Strong programming and automation skills, preferably Golang , with Python experience also valuable.

Strong debugging skills across Kubernetes, Linux, storage, virtualization .

Ability to mentor engineers, conduct automation/code reviews.

BS/MS with 8+ years of software testing/SDET experience , preferably involving distributed systems, infrastructure, storage, or virtualization.

Strong hands-on experience with Kubernetes and Kubernetes application lifecycle management.

Experience working with VMWare/HyperV , K ubeVirt or Red Hat OpenShift Virtualization is highly desirable.

Strong background in enterprise storage (file/block/Object) and Kubernetes persistent storage/CSI .

Strong Golang and/or Python programming skills , with Golang preferred.

Experience developing and maintaining automation frameworks and CI/CD pipelines .

Experience with Kubernetes platforms such as OpenShift, EKS, AKS, or GKE is a plus.

Working experience with public clouds such as AWS., Azure and Google Cloud is preferable.

Experience with tools such as Git, Jenkins/GitHub Actions, Jira, Confluence, X-ray is preferable.

📌 Software Developer - AI/ ML (Bengaluru)
🏢 Everpure
📍 Bengaluru