FolioX AI
Quality Assurance Engineer
Skills
14 days ago
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Important information
Contract type:
Permanent
Work mode:
Onsite
Published on:
10 October 2026
What they need
Company Description FolioX is building autonomous intelligence for dispatch and logistics, replacing manual planning with continuous, machine-driven decision-making. The company develops post-ERP, next-generation operational systems that use AI agents, reinforcement learning, and optimization to manage complex supply chains. FolioX’s software forecasts demand, plans inventory, and orchestrates routes autonomously across real-world logistics networks. Team members work on cutting-edge technologies that directly impact how businesses operate and optimize their logistics operations.
Role Description This full-time remote Quality Assurance Engineer role focuses on ensuring the reliability and performance of FolioX’s AI-driven logistics platforms. The Quality Assurance Engineer will design, write, and maintain test cases, execute manual and exploratory tests, and document issues clearly for engineering teams. Day-to-day responsibilities include validating new features, performing regression and integration testing, and collaborating with developers and product managers to refine requirements and improve product quality. The role also involves contributing to test plans, helping enhance QA processes and standards, and supporting continuous improvement in testing practices across the organization.
Qualifications
- Candidates should possess strong Quality Assurance and Software Testing skills, with experience applying structured QA methodologies.
- Candidates should possess Test Execution and Manual Testing skills, including hands-on functional, regression, and exploratory testing.
- Candidates should possess skills in designing and maintaining clear, reusable Test Cases aligned with product requirements.
- Candidates should ideally have experience with test management tools, bug tracking systems, and basic familiarity with automation frameworks.
- Relevant qualifications include a bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
- Additional beneficial skills include familiarity with AI or data-driven products, strong analytical thinking, attention to detail, and effective written and verbal communication.
- Ability to work independently in a remote setting, collaborate across time zones, and adapt to a fast-paced, evolving product environment.
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