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QA Engineer / Sr. QA Engineer - Machine Learning Platform for E-Commerce
AppIQ Technologies —México
- Tiempo completo
- Home Office (Desde casa)
- SQL
- Licenciatura
- JavaScript
- Vacaciones adicionales o permisos con goce de sueldo
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QA Engineer / Sr. QA Engineer - Machine Learning Platform for E-Commerce

AppIQ Technologies
México

Postulación rápida

Información del empleo

Tiempo completo

Beneficios

Vacaciones adicionales o permisos con goce de sueldo

Cualificaciones

Node.js
React
NoSQL
MongoDB
E-commerce
SQL
Garantía de calidad
Licenciatura
JavaScript
S3
TypeScript
Python

Descripción completa del empleo

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.

____________

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.

____________

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.

____________

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).

____________

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.

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