QA Engineer / Sr. QA Engineer - Machine Learning Platform for E-Commerce
Location
CET (UTC+1)
Posted
4 days ago
Salary
0
Seniority
Senior
Job Description
QA Engineer / Sr. QA Engineer - Machine Learning Platform for E-Commerce
AppIQ Technologies
Role Description 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. - Identify and prioritise 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 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. Qualifications - 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. Requirements - 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.
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