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You will be responsible for ensuring software quality through manual and automated testing, API validation, and the integration of AI-powered practices into the SDLC. The role involves collaborating with cross-functional teams to design test strategies, execute test plans, and drive continuous improvement in engineering efficiency.
Location: Remote / Pakistan
Department: Engineering & Product Delivery
Employment Type: Full-Time
Reports To: QA Lead / Engineering Manager
About AIM
AIM is a Canadian technology company that helps organizations modernize their systems through advanced API management, cloud engineering, security solutions, and full-stack software development. Our teams work across North America and globally, delivering stable, scalable, and secure digital platforms for enterprise clients.
We take pride in being hands-on, collaborative, and focused on delivering real results for our clients. As we continue to grow, we are expanding our teams across technology, operations, delivery, and business functions to support increasing client demand and drive the next stage of our growth.
Position Overview
We are seeking an Quality Assurance Engineer who combines strong software testing fundamentals with practical experience using Generative AI as part of the Software Development Lifecycle (SDLC).
This role is ideal for a QA professional who understands both traditional quality engineering principles and the evolving AI-assisted engineering landscape. You will be responsible for ensuring software quality through manual testing, automated testing, API validation, and AI-powered quality engineering practices.
The successful candidate will demonstrate the ability to leverage AI tools such as Claude, ChatGPT, Microsoft Copilot, or equivalent technologies to improve test design, accelerate automation, enhance defect discovery, and improve overall delivery quality.
Key Responsibilities
Manual & Functional Testing
API & Backend Testing
Test Automation
AI-Assisted Quality Engineering
Collaboration & Delivery
Required Qualifications
Mandatory Requirements
AI Quality Engineering Requirements
Candidates must demonstrate practical experience in:
Technical Skills
Quality Assurance
Automation
Tools & Platforms
Databases
Programming & Scripting
Preferred Qualifications
Preferred Certifications
Acceptable Microsoft Alternative
Note: AB-730 may be considered a supplementary credential but will not be accepted as the primary technical AI qualification.
Practical Assessment
All shortlisted candidates must successfully complete a practical assessment before progressing to final interviews.
AI-Assisted QA Assessment
Candidates must complete a 45 to 60-minute practical exercise demonstrating how they would use Claude (or an equivalent Generative AI platform) to quality assure an application.
The assessment will evaluate the candidate's ability to:
Success Profile
The ideal candidate:
✅ Thinks like a Quality Engineer rather than simply a tester.
✅ Understands how AI can enhance software quality without replacing engineering judgment.
✅ Can independently create test plans, automation scripts, and defect investigations.
✅ Has strong communication skills and can work directly with technical and business stakeholders.
✅ Takes ownership of quality outcomes and continuous improvement initiatives.
✅ Is excited about combining Quality Engineering and Artificial Intelligence to help deliver exceptional software experiences.
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