QA Automation Engineer with AI/ML
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Role details
Tech stack
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Job description
Develop and maintain automated test suites for secure access products using AI/ML techniques to improve test coverage and efficiency. Utilize AI/ML models to identify test case redundancies, optimize test execution, and predict potential failure points to reduce error rates in production. Collaborate with cross-functional teams to automate policy creation, testing, and troubleshooting of secure access features. Implement AI-driven analytics to detect advanced security threats and validate security controls within the secure access environment. Participate in the design and implementation of AI/ML-powered DevOps pipelines to enable autonomous testing and continuous integration/continuous deployment (CI/CD). Ensure compliance with security standards and best practices in AI/ML model usage and data handling. Monitor and analyze test results, providing actionable insights to improve product quality and security posture. Stay current with emerging AI/ML technologies and security trends relevant to secure access solutions.
Requirements
Experience in QA automation with strong programming skills in languages such as Python, Java, or similar. Knowledge of AI/ML concepts and practical experience applying AI/ML techniques in software testing or quality assurance. Familiarity with secure access technologies, zero-trust security models, and network security principles. Experience with AWS DevOps tools and CI/CD pipelines, preferably with AI/ML integration. Understanding of security risks related to AI/ML workloads and mitigation strategies. Strong analytical and problem-solving skills with attention to detail. Ability to work collaboratively in a fast-paced, cross-functional team environment.
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