QA Engineer / Sr. QA Engineer - Machine Learning Platform for E-Commerce

AppIQ Technologies develops a Machine-Learning-driven e-commerce funnel optimisation and digital advertising platform.

• 4+ years of professional experience in software quality assurance or engineering, with a strong focus on scalable web applications (7+ years for Sr. QA Engineer).
• Strong grasp of QA architecture and modern testing methodologies.
• Deep expertise in TypeScript, with strong architectural understanding of React and Node.js environments.
• Familiarity with AWS services and both SQL and NoSQL (e.g., MongoDB) databases.
• Ability to work effectively with globally distributed teams.

Strong Plus if You Have:

• Familiarity with Next.js.
• Proficiency in Vitest, Jest, or other unit and integration test solutions.
• Experience with Playwright, Cypress, or similar End-to-End testing tools.
• Understanding of Machine Learning (Supervised & Reinforcement Learning), Predictive AI, and validation of Data Pipelines.
• Proficiency in Python and experience with PySpark.
• Prior experience in e-commerce or Ad Tech ecosystems (Media Buying, DSPs, Conversion Optimisation).

QA Architecture & Strategy:

• Develop and maintain a comprehensive QA architecture that supports full-stack applications and complex microservices.

Risk Management:

• Prioritise bug fixes based on risk of failure and potential impact, balancing speed-to-market and exhaustive testing.

Test Management:

• Utilise test case management systems such as TestRail, Zephyr, Xray, PractiTest, qTest, or similar to organise test cases, track execution, and report on quality metrics.

Automated Testing:

• Design, implement, and scale automated test suites using tools such as Playwright, Cypress, and Appium or similar.

Testing & Validation:

• Design and execute integration, API, and End-to-End tests on applications built with TypeScript, React, Node.js, Python, and PySpark.
• Collaborate with developers to ensure adequate unit test coverage.

Infrastructure Testing:

• Verify reliability of deployments across AWS (EC2, S3, Firehose) and Cloudflare edge environments.

Data Integrity:

• Collaborate with Data Engineers to validate accuracy of complex event data and real-time reporting dashboards.

Cross-Functional Collaboration:

• Work closely with developers and data scientists to ensure a seamless end-user experience.