Junior QA Engineer - Machine Learning Platform for E-Commerce

AppIQ Technologies; France; À distance; EUR 50 000 - 70 000; Plein temps

Avantages offerts par ce poste

Competitive compensation

Generous paid time off

Work-from-anywhere flexibility

Learning and training opportunities

Résumé du poste

A leading technology company in France is seeking a meticulous QA Engineer / Sr. QA Engineer to ensure quality for its Machine-Learning-driven platform. Responsibilities include defining testing strategies, managing risks, and executing automated tests. Candidates should have at least 4 years in QA, familiarity with TypeScript, React, and AWS. The role offers competitive compensation, work-from-anywhere flexibility, and opportunities for professional growth.

Qualifications

• 4+ years of professional experience in software quality assurance or engineering, with a strong focus on scalable web applications.
• Strong grasp of QA architecture and modern testing methodologies.
• Deep expertise in the tech stack used by our engineers.

Responsabilités

• Develop and maintain a comprehensive QA architecture.
• Prioritise bug fixes based on risk of failure and potential impact.
• Utilise test case management systems to organise test cases.

Connaissances

QA architecture and modern testing methodologies

Automated testing with tools like Playwright, Cypress, Appium

Collaboration skills

Knowledge of TypeScript, React, Node.js, Python, PySpark

Risk management

Ability to work with globally distributed teams

Outils

TestRail

Zephyr

Xray

PractiTest

qTest

AWS

MongoDB

Description du poste

Overview

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 thorough testing and identify and prioritise the highest-risk bugs to ensure our scalable services, which manage millions of daily events, remain robust and accurate.

Responsibilities

• 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 balancing speed-to-market with 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.

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 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.