Lead QA Engineer

Global Payments Inc.; Alpharetta (GA); On-site; USD 90,000 - 120,000; Full time

Job summary

A leading financial technology company is seeking a Lead QA Engineer to enhance the quality of AI/ML models and systems. The ideal candidate has over 6 years of QA experience, proficient in Python and various AI/QA libraries. You'll be responsible for developing QA strategies, testing automation, and collaborating with engineering teams to validate AI outputs. This full-time role is based in Alpharetta, Georgia, and offers a dynamic environment in financial services and IT consulting.

Qualifications

• Minimum 6 years of experience in quality assurance, specifically testing AI/ML applications.
• Hands-on skills with Python and relevant AI/QA libraries.
• Strong understanding of software testing methodologies and best practices.

Responsibilities

• Develop and implement QA strategies tailored for AI/ML solutions.
• Create and maintain automated and manual test cases.
• Collaborate with AI engineers and data scientists.
• Perform regression, integration, stress, and adversarial testing.
• Document testing procedures and quality assessments.

Skills

Python

AI/ML testing

CI/CD tools

Docker

Kubernetes

Analytical skills

Communication

Education

Bachelor’s degree in Computer Science or Engineering

Tools

Pytest

TensorFlow

Jenkins

Git

Job description

Join to apply for the Lead QA Engineer role at Global Payments Inc.

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

Description

A QA Engineer (AI/ML) role in the Enterprise AI/ML Organization, reporting to the Leader of the 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 has worked closely with machine learning engineers and data scientists to ensure the quality and reliability of AI/ML models and systems.

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

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• Minimum 6 years of experience in quality assurance, specifically testing AI/ML applications.
• 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.

Seniority Level

• Mid‑Senior level

Employment Type

• Full‑time

Job Function

• Engineering and Information Technology

Industries

• Financial Services
• IT Services and IT Consulting

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