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Salary
$66k – $72k per year
Location
Remote (Croatia)
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 12, 2026. First seen by Alion on Sep 16, 2026.

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Newfire Global Partners is an American IT services and advisory firm (founded in 2016 in Boston) that provides talent augmentation, software engineering, data & analytics, and AI/ML advisory to enterprise and investor clients. The company offers multidisciplinary engineering, product, and marketing teams, technical due diligence for VC/PE, data platform optimization, and an internal ML tool (Novel Heat) to improve code quality and Scrum velocity. Newfire operates across the Americas, Europe, and APAC with a 24x5 follow-the-sun delivery model and focuses on sectors such as digital healthcare, fintech, cybersecurity, and education technology.

Newfire partners with leading global companies to drive long-term engineering transformations. On this project, we are working alongside a well-established company in the luxury retail industry undergoing a major technology shift across their digital ecosystem-including a custom e-commerce platform, multiple online storefronts, and ERP integrations. The objective is to modernize the platform and accelerate software delivery, taking release cycles from several months down to about one month.

Faster, high-confidence testing is central to this effort. Development on this project is AI-native, utilizing agentic development tools like Claude Code and CodeRabbit, with AI-assisted testing serving as a core mechanism to maximize test coverage efficiently.

About the Role

At Newfire, Quality Assistance focuses on enablement rather than serving as a downstream gatekeeper. Working under the QA Lead, you will build the frameworks, tooling, harnesses, and patterns that make it simple for every engineer to test their own work. You will extend the shared end-to-end suite across critical shopping journeys and build out automated API coverage to safeguard business operations.

Your success is measured by how effectively you enable engineers to test, rather than the number of bugs caught downstream. You will frequently map out expected feature behavior, establish documented sources of truth, and maintain test code to the same rigorous standards as production code.

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