Principal Software Quality Engineer

JOB SUMMARY

We are seeking a Principal Software Quality Engineer to lead and drive our quality assurance efforts across web, mobile, and AI/ML-powered applications. This role is pivotal in ensuring the reliability, performance, scalability, and intelligence of our supply chain management platform. You will architect innovative testing strategies, incorporating cutting-edge ML/AI tools, to proactively identify issues and enhance our automated testing capabilities. Your leadership will ensure that our platform continues to set industry standards in quality and reliability.

Responsibilities:

• Test Automation Frameworks:
• Architect and implement advanced, scalable test automation frameworks for web, mobile, and AI/ML-powered applications.
• Ensure seamless integration of these frameworks with Kubernetes-based microservices.
• Device Farm Management:
• Design and manage cloud-based and on-premises device farms to enable robust testing across various mobile devices, operating systems, and configurations.
• Comprehensive Testing Strategies:
• Develop testing strategies that encompass functional, performance, security, regression, and AI/ML validation for complex supply chain systems.
• Leverage AI/ML algorithms to generate dynamic and intelligent test cases, predict potential issues, and enhance test execution efficiency.
• CI/CD and Quality Gates:
• Implement CI/CD pipelines with rigorous quality gates to uphold high standards in software delivery.
• AI/ML Testing Integration:
• Design and execute test plans for AI/ML models, focusing on aspects such as accuracy, bias, scalability, and drift.
• Integrate ML-driven tools to monitor and validate AI system behavior in real-time.
• Mentorship and Collaboration:
• Mentor and guide QA team members in adopting modern testing methodologies and ML/AI-based tools.
• Collaborate with cross-functional teams, including development, data science, and product management, to ensure quality throughout the development lifecycle.
• Risk-Based Testing:
• Implement risk-based testing strategies to optimize resources and prioritize high-impact scenarios in supply chain operations.
• Quality Metrics and Reporting:
• Establish and monitor metrics to track quality trends, identify improvement areas, and communicate results to stakeholders.

What You Bring:

Core QA Expertise:

• 12+ years of experience in software quality assurance, with strong expertise in web, mobile, and AI/ML application testing.
• Proven expertise in test automation tools such as Selenium, Appium, TestNG, and AI/ML-driven frameworks.

Programming and Automation:

• Strong programming skills in Java and Python; familiarity with JavaScript or Groovy is a plus.
• Hands-on experience designing custom test automation frameworks tailored to business needs.

Device Farms and Cloud Platforms:

• Expertise in setting up and managing device farms using platforms like BrowserStack, Sauce Labs, or AWS Device Farm.
• Deep understanding of cloud platforms (AWS, GCP, or Azure) and containerized environments (Kubernetes).

AI/ML Testing:

• Experience in validating AI/ML models, including performance, accuracy, fairness, and bias testing.
• Familiarity with AI-driven testing tools (e.g., Test.ai, Applitools) and predictive analytics to enhance quality assurance processes.

Continuous Integration and DevOps:

• Proficiency in CI/CD tools and workflows, including integration of quality gates and automated testing pipelines.

Analytical Skills:

• Strong analytical skills with a data-driven approach to problem-solving and decision-making.

Nice to Have:

• Stay updated with the latest trends in QA, AI/ML technologies, and supply chain innovations, applying these advancements to testing processes.
• Develop and automate performance testing strategies for supply chain applications under high-load conditions.
• Implement intelligent security testing protocols to ensure compliance with industry standards.
• Innovate test data management strategies using synthetic data generation and AI/ML to maintain data privacy while ensuring test coverage.
• Continuously evaluate and implement tools, frameworks, and processes to enhance quality assurance efficiency.