ABOUT IRTH SOLUTIONSIrth 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 OPPORTUNITYWe 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 RESPONSIBILITIESOwn the full QA lifecycle for assigned features and releases — from requirements review through test planning, execution, defect tracking, and sign-offDesign, develop, and maintain comprehensive test plans, test cases, and test suites that cover functional, regression, integration, and edge-case scenariosBuild, maintain, and scale automated test frameworks and scripts using open-source and enterprise - tooling reducing manual effort and increasing confidencePerform exploratory, functional, regression, performance, and API testing across our ASP.NET / SQL Server / Azure-hosted SaaS platformReview system requirements, user stories, and technical design documents early in the development cycle to surface risks and provide meaningful QA feedbackCollaborate closely with developers, product managers, and data engineers to identify, document, reproduce, and verify resolution of defectsMonitor and report on QA metrics - defect density, test coverage, open defect counts, and release readiness - to keep the team data-informedInvestigate root causes of non-conforming software and drive process improvements to prevent recurrenceStay current with evolving QA methodologies, tools, and industry trends — especially in automation, AI-assisted testing, and SaaS quality practices
