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

**Company:** [AppIQ Technologies](http://jobs.workable.com/companies/1wmgZ5nWwYiRVE2bmocPtX.md)
**Location:** Remote
**Workplace:** remote
**Employment type:** Full-time
**Department:** Engineering & Technical

[Apply for this job](http://jobs.workable.com/view/0503013e-60fa-4ad9-a43c-fa820b871f7d)

## 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.

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.

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### **Responsibilities**

●      **QA Architecture & Strategy**: Develop and maintain a comprehensive QA architecture that supports full-stack applications and complex microservices.

●      **Risk Management**: Prioritize bug fixes based on risk of failure and potential impact, while striking a productive balance between speed-to-market and exhaustive testing.

●      **Test Management**: Utilize test case management (TCM) systems such as TestRail, Zephyr, Xray, PractiTest, qTest, or similar (your choice) to organize 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.

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## 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.

●      Basic knowledge of **Python**

●      **Global Collaboration**: Ability to work effectively with globally distributed teams.

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### **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**.

●      Experience with **Restricted Boltzmann Machines (RBM)** for e-commerce funnel feature extraction.

●      Prior experience in the **e-commerce** or **Ad Tech** ecosystems (Media Buying, DSPs, Conversion Optimization).

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## 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.