AI Quality Automation Engineer , DTG

Pure Storage

Location not specified

Full Time

Posted August 5, 2026

$76k - $110k· Est.

Power Generation

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Job Description

And because we understand the value of bringing your full and best self to work, we offer a variety of perks to manage a healthy balance, including flexible time off, wellness resources, and company-sponsored team events.

Key Responsibilities

Be a Steward of the QA Process & Platform: Help evolve the QA process, automation platform, and quality practices across MDM, ensuring testing is embedded throughout the development lifecycle.
Build AI-Powered Quality Frameworks: Develop and execute automated test suites and AI-enabled evaluation frameworks to detect data anomalies early, validate pipeline logic, and reduce manual quality overhead across enterprise data infrastructure.
Expand the E2E AI Testing Platform: Contribute to and improve our end-to-end testing platform, using generative AI and emerging AI capabilities to increase test coverage and accelerate delivery for core MDM applications.
Explore Agentic Development Automation: Experiment with AI agents and agentic development workflows to automate parts of testing, test creation, validation, troubleshooting, and the broader software development lifecycle.
Bring a New AI Perspective to QA: Identify and experiment with practical ways AI can improve Quality Engineering. Bring curiosity, ideas, and an enthusiasm for AI rather than simply applying traditional testing approaches.
Automate Continuous Integration Pipelines: Build and maintain CI/CD workflows using GitHub Actions to automate testing and support reliable MDM software delivery.
Drive Data Precision & Governance: Partner with cross-functional engineering teams to develop automated quality checks, test plans, and validation metrics that safeguard enterprise data integrity.
Enhance Operational Telemetry & Observability: Integrate automated telemetry and monitoring into existing CI/CD pipelines to improve observability, identify issues earlier, and support root-cause analysis.

Requirements

Experience: 2+ years of professional experience in Quality Engineering, test automation, software engineering, or data platform testing.
Python & Automation: Hands-on experience with Python coding and building automated tests, test frameworks, API automation, or data validation solutions.
AI Enthusiasm: Strong interest in AI and how it can transform Quality Engineering and software development. Hands-on exposure to generative AI, LLMs, AI-assisted development, or agentic workflows is a plus; deep AI expertise is not required.
Quality Engineering Mindset: A strong understanding of QA and automated testing, with an interest in improving the overall quality process, platform, and tooling.
Collaboration & Problem Solving: Ability to investigate technical issues, find practical solutions, and work effectively with software, data, and quality engineering teams.
Location: We are primarily an in-office environment and therefore, you will be expected to work from the Prague, Czech Republic office in compliance with Pure’s policies, unless you are on PTO, work travel, or other approved leave.
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