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# QA Automation Engineer

- **Company:** Tata Consultancy Services Limited
- **Location:** San Jose, CA, United States
- **Salary:** $100,000.0 - $130,000.0
- **Contract:** Permanent contract
- **Skills:** Testing (Software), Java (Programming Language), Artificial Intelligence, Automation of Tests, Code Coverage, Computer Programming, Continuous Delivery, Continuous Integration, DevOps, Python (Programming Language), Network Security, Machine Learning, Zero Trust Network Access, Test Case, Test Execution Engine, Data Processing, Delivery Pipeline, Machine Learning Operations
- **Published:** September 30, 2026
- **Apply:** https://www.dice.com/job-detail/34ba58cb-d7f4-4681-88fd-0046801260e0

## About the Role

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.

## 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.
"


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