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

AppIQ Tech is seeking a meticulous and strategic QA Engineer / Sr. QA Engineer to ensure the quality and reliability of our Machine-Learning-driven e-commerce funnel optimisation and digital advertising platform.

You will be responsible for defining the testing strategy for high-performance applications that leverage our proprietary Predictive AI solutions.

As a key member of our fast-paced startup, you will balance the need for rapid feature deployment with the necessity of thorough testing. You will be responsible for identifying and prioritising the highest-risk bugs to ensure our scalable services, which manage millions of daily events, remain robust and accurate.

• 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, while striking a productive balance between speed-to-market and exhaustive testing.

• Test Management: Utilise test case management (TCM) systems such as TestRail, Zephyr, Xray, PractiTest, qTest, or similar to organise test cases, track execution, and provide transparent reporting on quality metrics.

• Automated Testing: Design, implement, and scale automated test suites using tools such as Playwright, Cypress, and Appium.

• Testing & Validation: Perform rigorous unit tests and integration tests on applications built with TypeScript, React, Node.js, Python, and PySpark.

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

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

• Cross-Functional Collaboration: Act as a great team player with excellent communication skills, working closely with developers and data scientists to ensure a seamless end-user experience.

Requirements:
• 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 the tech stack used by our engineers, specifically TypeScript, React, Node.js, Python, and PySpark.

• Cloud & Database Proficiency: Familiarity with AWS services and both SQL and NoSQL (e.g., MongoDB) databases to effectively test data persistence and performance.

• Global Collaboration: Ability to work effectively with globally distributed teams.
• Native or Business-level proficiency in written and spoken English

Strong plus if you also have:

• AI/ML Literacy: Understanding of Machine Learning (Supervised/Reinforcement Learning), Predictive AI, and the validation of Data Pipelines.

• Proficiency in Python or experience with PySpark.

• Prior experience in the e-commerce or Ad Tech ecosystem (DSPs, Audience Data, Fraud detection).

Benefits:
• The opportunity to shape the QA culture and architecture from the ground up.

• An attractive career path on either a management or an individual contributor track.
• Genuine learning, training and development opportunities, supported by regular performance reviews

• Competitive compensation and generous paid time off.

• Work-from-anywhere flexibility

• Opportunities to develop expertise in building cutting-edge predictive AI applications.