QA Engineer - Machine Learning Platform for E-Commerce

AppIQ Tech; France; Remote; EUR 60,000 - 90,000; Full time

Benefits offered by this job

The opportunity to shape QA culture

Career path on management or IC track

Learning and development opportunities

Competitive compensation and generous休

Work-from-anywhere flexibility

Growth in predictive AI applications

Job summary

AppIQ Tech is seeking a meticulous QA Engineer / Senior QA Engineer to ensure the quality and reliability of our ML-driven e-commerce funnel optimization and digital advertising platform.

You will define testing strategy for high-performance applications built with TypeScript, React, Node.js, Python, and PySpark, leveraging AWS and Cloudflare edge deployments. Work closely with developers and data scientists to deliver robust, scalable services and accurate real-time dashboards.

Qualifications

• 4+ years of experience in software QA or engineering for scalable web apps.
• Sr. QA Engineer: 7+ years of experience in QA.
• Strong grasp of QA architecture and testing methodologies.
• Proficiency with TypeScript, React, Node.js, Python, and PySpark.

Responsibilities

• Define testing strategy for high-performance apps and microservices.
• Prioritize bugs by risk and impact for rapid yet robust releases.
• Design and scale automated tests with Playwright, Cypress, and Appium.
• Coordinate testing across AWS, Cloudflare, and data pipelines with engineers.

Skills

QA architecture

Testing methodologies

TypeScript

React

Node.js

Python

PySpark

AWS

SQL

NoSQL

English communication

Tools

TestRail

Zephyr

Xray

PractiTest

qTest

Playwright

Cypress

Appium

Job description

AppIQ Tech 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 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.
• Testing & Validation: Perform rigorous unit tests and integration tests on applications built with TypeScript, React, Node.js, Python, and PySpark.
• 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 the tech stack used by our engineers, specifically TypeScript, React, Node.js, Python, and PySpark.
• 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.
• Native or Business-level proficiency in written and spoken English

Strong plus if you also have:

• AI/ML Literacy: Understanding of Machine Learning (Supervised/Reinforcement Learning), Predictive AI, and the validation of Data Pipelines.
• Proficiency in Python or experience with PySpark.
• Prior experience in the e-commerce or Ad Tech ecosystem (DSPs, Audience Data, Fraud detection).

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.
• Genuine learning, training and development opportunities, supported by regular performance reviews
• Competitive compensation and generous paid time off.
• Work-from-anywhere flexibility
• Opportunities to develop expertise in building cutting-edge predictive AI applications.