Lead QA Engineer (Artificial Intelligence)

Every day Global Payments makes it possible for millions of people to move money between buyers and sellers using our payments solutions for credit debit prepaid and merchant services. Our worldwide team helps over 3 million companies more than 1300 financial institutions and over 600 million cardholders grow with confidence and achieve amazing results. We are driven by our passion for success and we are proud to deliver best-in-class payment technology and software solutions. Join our dynamic team and make your mark on the payments technology landscape of tomorrow.

At this time we are unable to offer visa sponsorship for this position(H1b/OPT). Candidates must be legally authorized to work for any employer in the United States (or (applicable country) on a full-time basis without the need for current or future immigration sponsorship

QA Engineer (AI/ML) (Exempt)

Enterprise AI/ML Organization

Reports to Leader of ML Engineering Group

OVERVIEW

This QA Engineer position is for a hands-on professional with experience in testing and automating AI/ML pipelines. The ideal candidate is someone who has worked closely with machine learning engineers and data scientists to ensure the quality and reliability of AI/ML models and systems. You will join a dynamic team passionate about innovation learning and applying cutting-edge technologies to deliver high-quality AI solutions.

RESPONSIBILITIES

• Develop and implement QA strategies tailored for AI/ML solutions including models APIs pipelines and agent-based architectures.

• Create and maintain automated and manual test cases for model validation (accuracy bias robustness explainability drift).

• Collaborate with AI engineers data scientists and product teams to define success criteria acceptance standards and performance metrics.

• Validate model outputs and system behaviors against business and ethical guidelines.

• Perform regression integration stress and adversarial testing of AI models and systems.

• Identify log and track bugs and anomalies ensuring timely resolutions.

• Support monitoring production AI systems to detect model performance degradation (concept drift data drift hallucinations).

• Ensure compliance with internal AI governance standards responsible AI principles and regulatory requirements.

• Contribute to building automated AI testing frameworks pipelines and synthetic data generation systems.

• Document testing procedures results and quality assessments clearly and effectively.

Must Haves:

• Bachelors degree in Computer Science Engineering or a related field.

• Minimum 6 years of experience in quality assurance specifically testing AI/ML applications.

• Experience with the following:

  • Hands-on skills with Python and relevant AI/QA libraries (Pytest Unittest Great Expectations MLflow Deepchecks etc.).

  • Familiarity with machine learning frameworks (TensorFlow PyTorch or scikit-learn).

  • Experience with test automation tools and frameworks.

  • Knowledge of CI/CD tools (Jenkins GitLab CI or similar).

  • Experience with containerization technologies like Docker and orchestration systems like Kubernetes.

  • Familiarity with version control systems like Git.

• Strong understanding of software testing methodologies and best practices.

• Excellent analytical and problem-solving skills.

• Excellent communication and collaboration skills.

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