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

Description

Summary: AppIQ Technologies seeks a meticulous and strategic QA Engineer/Sr. QA Engineer to define testing strategies for high-performance applications leveraging proprietary Predictive AI solutions, balancing rapid deployment with thorough testing. Highlights: 1. Shape the QA culture and architecture from the ground up 2. Attractive career path (management or individual contributor) 3. Develop expertise in cutting-edge predictive AI applications AppIQ Technologies 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 (your choice) 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** or similar tools. **Testing \& Validation:** Design and execute rigorous 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 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 **TypeScript**, alongside a strong architectural understanding of **React and Node.js** environments. **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. **Strong Plus if You Have:** Familiarity with **Next.js** Proficiency in **Vitest** , **Jest** or other unit and integration test solutions. Experience with **Playwright** or **Cypress** or similar End\-to\-End testing tools. **AI/ML Literacy**: Understanding of **Machine Learning (Supervised \& Reinforcement Learning)**, Predictive AI, and the validation of **Data Pipelines**. Proficiency in **Python** and experience with **PySpark**. Prior experience in the **e\-commerce** or **Ad Tech** ecosystems (Media Buying, DSPs, Conversion Optimisation). **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. **Competitive compensation** and generous paid time off. **Remote work flexibility** allows you to work from nearly anywhere on Earth, provided you can maintain a few overlapping hours with Central European Time (CET). **Opportunity to develop deep expertise in creating and testing cutting\-edge predictive AI applications,** which goes far beyond using other companies’ AI tools.