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

AppIQ Technologies is seeking a meticulous and strategicQA 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 asPlaywright, Cypress, and Appiumor 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 adequateunit testcoverage.

Infrastructure Testing: Verify the reliability of deployments acrossAWS (EC2, S3, Firehose) andCloudflare 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 agreat team player withexcellent communication skills, working closely with developers and data scientists to ensure a seamless end-user experience.

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 inTypeScript, alongside a strong architectural understanding of React and Node.js environments.

Cloud & Database Proficiency: Familiarity withAWS services and bothSQL 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 withNext.js

Proficiency inVitest,Jestor other unit and integration test solutions.

Experience withPlaywright orCypressor similar End-to-End testing tools.

AI/ML Literacy: Understanding ofMachine Learning (Supervised & Reinforcement Learning), Predictive AI, and the validation ofData Pipelines.

Proficiency inPython and experience withPySpark.

Prior experience in thee-commerce orAd Tech ecosystems (Media Buying, DSPs, Conversion Optimisation).

The opportunity toshape the QA culture and architecture from the ground up.

Anattractive 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.