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Salary
≈ $21k – $49k per year (Estimated)
Location
In office (India)
Experience
8+ years exp

First seen by Alion on Oct 23, 2026. Everpure scores A on the Alion truth index.

Overview
Company
Impact
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Everpure is an enterprise data management and storage platform company - formerly known as Pure Storage - headquartered in Santa Clara, California. The company specializes in all-flash data storage, cloud-native storage management, and AI infrastructure designed to help organizations consolidate, protect, and scale their data operations across hybrid and multi-cloud environments.

Job Description :


We're looking for engineers passionate about system testing, distributed systems, Kubernetes, storage, modern virtualisation, 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 modernise 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 containerised applications, KubeVirt/OpenShift Virtualisation VMs, and demanding AI/ML workloads running on Kubernetes.

Responsibilities :

- Own system-level quality for Portworx Enterprise across Kubernetes, storage, and modern virtualisation 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.

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

Requirements :

- 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, and virtualisation.

- Ability to work on multiple concurrent product/feature releases.

- Excellent communication and collaboration skills with the ability to work effectively across geographically distributed teams.

- Ability to mentor engineers and conduct automation/code reviews.

- BS/MS with 8 - 12 years of software testing/SDET experience, preferably involving distributed systems, infrastructure, storage, or virtualisation.

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

- Experience working with VMWare/HyperV, KubeVirt or Red Hat OpenShift Virtualisation 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, and X-ray is preferable.

Skills

SDET, System Testing, Distributed Systems, Kubernetes, Virtualization, Product Testing, VMware, Hyper-V, IT Infrastructure, Python, CI/CD Pipeline

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