QA Assurance Analyst

ABOUT IRTH SOLUTIONS Cobalt Streamworks 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 Cobalt Streamworks 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 Originally posted on Himalayas