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ScienceLogic is seeking a QA Automation Engineer to drive automated testing and CI/CD practices across our IT operations management platform. The role focuses on Python-based test automation, AWS and VMware environments, and collaboration with software engineers to ensure robust, scalable solutions.
The ideal candidate will be capable of designing test plans, reading Python code, and contributing to both manual and automated testing efforts in a fast-paced agile setting.
ScienceLogic is redefining IT operations for the modern enterprise. Our AIOps platform empowers organizations to achieve Autonomic IT - where systems are self-healing, self-optimizing, and seamlessly aligned with business outcomes. We help enterprises and service providers gain unified visibility across hybrid and multi-cloud environments, automate workflows, and unlock performance at scale.
We're accelerating digital transformation through the power of automation, AI, and analytics - giving IT and business leaders the tools to deliver superior customer experiences, drive efficiency, and innovate with confidence.
Don't meet every single requirement? Studies have shown that women and people of color are less likely to apply to jobs unless they meet every single qualification. At ScienceLogic, we are dedicated to building a diverse, inclusive and authentic workplace, so if you're excited about this role but your past experience doesn't align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or any other applicable legally protected characteristics in the location in which you are applying.
ScienceLogic is a leader in IT Operations Management, providing modern IT operations with actionable insights to resolve and predict problems faster in a digital, fleeting world. Its solution sees everything across cloud and distributed architectures, contextualizes data through relationship mapping, and acts on this insight through integration and automation.