QA Engineer, Machine Learning Platform – E-Commerce

This is a fully remote position, open to applicants in Mexico.

📋 Description

• AppIQ Technologies is on the lookout for a detail-oriented and strategic **QA Engineer / Sr. QA Engineer** to guarantee the quality and dependability of our Machine-Learning-driven e-commerce funnel optimization and digital advertising platform.

• You will take charge of establishing the testing strategy for high-performance applications that utilize our proprietary Predictive AI solutions.

• As an essential member of our dynamic startup, you will juggle the requirements for swift feature deployment with the importance of thorough testing.

• Your responsibilities will include identifying and prioritizing the most critical bugs to ensure that our scalable services, which handle millions of daily events, remain robust and precise.

• **QA Architecture & Strategy**: Develop and sustain a comprehensive QA architecture that supports full-stack applications and intricate microservices.

• **Risk Management**: Prioritize bug fixes based on the likelihood of failure and potential impact while maintaining a productive balance between speed-to-market and thorough testing.

• **Test Management**: Employ test case management (TCM) systems such as TestRail, Zephyr, Xray, PractiTest, qTest, or similar (your choice) to organize test cases, track execution, and deliver transparent reporting on quality metrics.

• **Automated Testing**: Create, implement, and scale automated test suites using tools such as **Playwright, Cypress, and Appium** or similar tools.

• **Testing & Validation**: Design and perform rigorous integration, API, and End-to-End tests on applications developed with TypeScript, React, Node.js, Python, and PySpark.

• Collaborate with developers to ensure adequate **unit test** coverage.

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

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

• **Cross-Functional Collaboration**: Be an effective **team player** with **excellent communication skills**, cooperating 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 significant emphasis on scalable web applications (7+ years for Sr. QA Engineer).

• **Strong understanding of QA architecture** and contemporary testing methodologies.

• Extensive expertise in **TypeScript**, with a solid architectural comprehension of **React and Node.js** environments.

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

• **Global Collaboration**: Capability to work efficiently 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 Knowledge**: Insight into **Machine Learning (Supervised & Reinforcement Learning)**, Predictive AI, and the validation of **Data Pipelines**.

• Proficiency in **Python** and experience with **PySpark**.

• Previous experience in the **e-commerce** or **Ad Tech** sectors (Media Buying, DSPs, Conversion Optimization).

🏝️ Benefits

• The chance to **shape the QA culture and architecture** from the ground up.

• An **attractive career path** available on either a management or individual contributor track.

• **Competitive compensation** and generous paid time off.

• **Remote work flexibility** allows you to work from almost anywhere in the world, 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**, moving beyond simply using other companies’ AI tools.