Software Quality Assurance Engineer
Job Description
Key Responsibilities :
– Validate Physics AI capabilities : Work closely with AI/ML engineers to understand the underlying physics models, simulation workflows, and algorithms, and validate the accuracy, robustness, fidelity, and consistency of AI predictions against traditional solver or reference results.
– Own end-to-end quality : Drive QA activities across the software development lifecycle, independently planning and executing quality activities to ensure reliable delivery of AI-enabled simulation capabilities.
– Design comprehensive testing : Review user stories, requirements, and design documentation for testability and develop functional, stress, performance, and end-to-end test scenarios aligned with engineering use cases.
– Develop and maintain test automation : Create, execute, and maintain automated tests using scripting and automation frameworks, while improving existing test suites and porting automation to high-performance systems where appropriate.
– Investigate complex technical issues : Go beyond identifying defects by reproducing issues, analyzing logs and system behavior, investigating root causes, and collaborating with Development and AI/ML teams to drive resolution.
– Improve quality engineering practices : Identify potential risks proactively, research complex problems, introduce effective solutions, and champion best practices in software quality, automation, and testing of Physics AI capabilities.
– Collaborate across engineering teams : Work closely with Development, AI/ML Engineering, DevOps, Product Management, Applications Engineering, and other teams in a globally distributed environment.
Qualifications :
– 4 to 6+ years of relevant technical experience in CAE, engineering simulation, design verification, Physics AI, Engineering AI, or a related domain, along with hands-on experience in Software Quality Engineering or software validation.
– 13+ years of professional experience in Software QA, Quality Engineering, software testing, or test automation, preferably for complex engineering or desktop software products.
– Strong understanding of CAE and engineering simulation workflows, with the ability to analyze simulation results and assess their technical and physical reasonableness.
– Exposure to AI/ML or Engineering AI, with the ability to understand and validate AI-driven predictions against physics-based, simulation, or solver-generated reference results.
– Experience with desktop simulation or engineering software such as Simcenter, CAD/CAE applications, or similar products; experience with HyperView, Simcenter 3D Post, or equivalent post-processing tools is highly valuable.
– Proficiency in Python, C, or similar scripting/programming languages, with hands-on experience developing or maintaining automated tests using PyTest, Ranorex, Selenium, or comparable frameworks.
– Strong analytical, problem-solving, communication, and collaboration skills, with the ability to work independently, investigate complex technical issues, and contribute effectively in cross-functional teams.
Preferred Skills :
– Experience testing or validating AI/ML models, Physics AI, surrogate models, or AI-enabled engineering applications.
– Experience comparing AI predictions with traditional CAE/CFD/FEA solver results, experimental data, or other engineering reference data.
– Familiarity with Windows and UNIX/Linux environments and cross-platform desktop software testing.
– Experience with JIRA, Xray, Git, and modern test automation frameworks.
– Experience with functional, regression, stress, performance, and system-level testing.
– Strong attention to detail, curiosity, self-motivation, and the ability to quickly learn unfamiliar engineering and software technologies.
Are you interested in this position?
Apply by clicking on the âApply Nowâ button below!
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