QA Assurance Analyst

ABOUT IRTH SOLUTIONS

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 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