ABOUT IRTH SOLUTIONS Irth Solutions is a market-leading SaaS technology company delivering cloud-based critical infrastructure management solutions to energy, utility, and telecom operators across North America. Our Asset Integrity for Pipelines (AIP) platform transforms how pipeline operators manage integrity data — combining machine learning, advanced data science, GIS integration, and enterprise analytics to drive safer, smarter decision-making across the full pipeline lifecycle. THE OPPORTUNITY We are looking to fill a full-time Quality Assurance Analyst, remote-work position. Working as part of the Irth AIP engineering team, you will play a central role in ensuring the quality and reliability of our enterprise SaaS platform — used by pipeline operators across North America to make critical safety and integrity decisions. The ideal candidate is detail-obsessed, technically sharp, and passionate about quality as a craft — not just a gate. You thrive in an agile environment, can hold your own in conversations with developers and product managers alike, and bring a mindset of continuous improvement to everything you do. Experience with test automation is essential; exposure to AI-driven testing approaches is a strong differentiator. KEY RESPONSIBILITIES • Own the full QA lifecycle for assigned features and releases — from requirements review through test planning, execution, defect tracking, and sign-off • Design, develop, and maintain comprehensive test plans, test cases, and test suites that cover functional, regression, integration, and edge-case scenarios • Build, maintain, and scale automated test frameworks and scripts using open-source and enterprise - tooling reducing manual effort and increasing confidence • Perform exploratory, functional, regression, performance, and API testing across our ASP.NET / SQL Server / Azure-hosted SaaS platform • Review system requirements, user stories, and technical design documents early in the development cycle to surface risks and provide meaningful QA feedback • Collaborate closely with developers, product managers, and data engineers to identify, document, reproduce, and verify resolution of defects • Monitor and report on QA metrics - defect density, test coverage, open defect counts, and release readiness - to keep the team data-informed • Investigate root causes of non-conforming software and drive process improvements to prevent recurrence • Stay current with evolving QA methodologies, tools, and industry trends — especially in automation, AI-assisted testing, and SaaS quality practices
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