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

AppIQ Technologies; Colombia; A distancia; COP 110.152.377 - 183.587.296; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Competitive compensation

Generous paid time off

Work-from-anywhere flexibility

Learning and development opportunities

Descripción de la vacante

A dynamic tech startup is seeking a meticulous QA Engineer to ensure the quality of their Machine-Learning-driven platform. The role involves developing comprehensive QA architecture, prioritising bug fixes based on risk, and implementing automated testing. Candidates should have 4+ years of experience in software QA with a strong grasp of modern testing methodologies and tech stacks including TypeScript and AWS. This position offers competitive compensation, generous paid time off, and work-from-anywhere flexibility.

Formación

• 4+ years of professional experience in software quality assurance or engineering.
• Strong grasp of QA architecture and modern testing methodologies.
• Deep expertise in TypeScript, React, Node.js, Python, and PySpark.
• Familiarity with AWS services and database testing.

Responsabilidades

• Develop and maintain a comprehensive QA architecture.
• Prioritise bug fixes based on risk and impact.
• Utilise test case management systems to track quality metrics.
• Design and scale automated test suites.

Conocimientos

QA architecture and modern testing methodologies

TypeScript

React

Node.js

Python

PySpark

AWS services

SQL and NoSQL databases

Automated testing tools (Playwright, Cypress, Appium)

Test case management systems

Descripción del empleo

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.