Quality Assurance (QA) Engineer

Array is a financial innovation platform that helps digital brands, financial institutions, and fintechs get compelling consumer products to market faster. We deliver a suite of credit and identity monitoring tools, privacy protection, and a financial ads marketplace via embeddable widgets or a clean, modern API.  Our private label offerings help drive revenue and increase engagement for our customers while empowering millions of consumers to achieve their financial goals.

As a remote-first company, we’re focused on providing opportunities for high performing individuals to have deep impact in the fast growing fintech space. A clear mission, a commitment to continuous improvement and a willingness to experiment empower us individually and together deliver the best products for our clients and users.

As a Quality Assurance Engineer at Array, you will ensure the quality, reliability, and performance of products that impact millions of users. You will support our engineers in their effort to ship code that is reliable and scalable. This role will report to a senior director of engineering. 

• Collaborate with the squads that are building apps in Go, Node.js, and other stacks to ensure end-to-end quality.
• Build and maintain automated test frameworks for APIs, microservices, and user-facing features.
• Debug, troubleshoot, and resolve issues with engineers to keep releases fast and reliable.
• Embed automated testing into CI/CD pipelines to raise confidence at scale.
• Grow as an expert in testing distributed systems, performance, and cross-environment reliability.
• Maintain a habit of using AI tools to think, build, and ship faster.

• Experience testing across multiple stacks (Go, Node.js, Java, C#) in fast-moving teams.
• A track record of building automated test frameworks for production systems.
• Familiarity with cloud platforms (AWS, Azure, or GCP) and securing apps at scale.
• An instinct for using Generative AI (Copilot, LLM agents) to write cases, generate data, and speed coverage without losing sight of the human element. 
• Hands-on with containerized environments (Docker, Kubernetes) and CI/CD pipelines.
• Proficiency with databases (Postgres, SQL Server, MongoDB) for validating data and backend quality.