QA Automation Engineer with AI/ML

Must Have Technical/Functional Skills

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.

Roles & Responsibilities

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.