About the job
The Ring Blink Customer Service (RBCS) team's application complexity has grown significantly, now serving thousands of external users 24/7 across multiple integrated platforms. We're rapidly deploying AI across voice, chat, and self-service channels, but our AI capabilities ship faster than we can validate them manually, creating a critical gap in our quality assurance process. The current testing team is overwhelmed with manual testing efforts, causing delays in release cycles and increasing the risk of production issues. Key challenges include managing multiple parallel releases, ensuring comprehensive integration testing across four major systems, maintaining high availability requirements (99.9% uptime), and meeting strict security compliance standards. We are seeking a Software Development Engineer in Test to establish and own the automated quality layer using AccelQ and other Amazon internal test automation tools, enabling us to ship AI features with confidence instead of slowing down to manually test every model change. This role will implement robust automation frameworks, conduct thorough integration testing, and ensure quality across all platforms. Without this crucial hire, we risk increased production incidents, delayed AI feature releases, customer dissatisfaction, team burnout, and technical debt accumulation. This role will be instrumental in supporting our business objectives of maintaining high system reliability, ensuring secure transactions, and enabling faster time to delivery of new AI-powered features.
Responsibilities
Write secure, stable, testable, maintainable code that consistently meets high quality standards; Design, develop, and execute comprehensive test automation frameworks using AccelQ and Amazon internal test automation tools for web applications, APIs, and integrated systems; Dive deep into testing methodologies to transform manual quality processes into highly automated quality solutions, specifically targeting AI validation bottlenecks; Own the end-to-end testing strategy across Salesforce, Amazon Connect, AI services, and AWS platforms; Conduct performance testing and capacity planning for high-traffic customer service applications and AI services; Communicate technical concepts and processes using clear, simple language and visuals
Qualifications
Minimum
3+ years of non-internship professional software development testing experience; Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design; Experience in penetration testing and exploitability-focused vulnerability assessment; Experience in platform-level security mitigations and hardening for Linux and Windows; 1+ years of test automation frameworks and tools building experience; 4+ years of test automation frameworks and tools building experience; Knowledge of at least one object-oriented language (e.g., Java, Python); Familiar with software engineering best practices for the full software development life cycle; Familiar with software test techniques and strategy; Familiarity with CI/CD frameworks, processes and tools for continuous testing and integration; Experience with both on-premises and cloud-based testing environments, preferably including AWS services
Preferred
Knowledge of overall system architecture, scalability, reliability, and performance in a database environment; Experience with security in service-oriented architectures and web services; Experience with test automation framework or tools (e.g., Junit, TestNG, Selenium); Experience with AccelQ or similar enterprise test automation platforms; Familiarity with Amazon internal test automation tools and testing frameworks; Knowledge of industry standard test automation tools and experience developing product test frameworks; Knowledge of scripting languages (bash, python, etc.); Experience with open source tools and resources; Experience automating the validation of modern user interfaces and infrastructures; Experience communicating technical concepts and processes using clear, simple language and visuals; Experience in Agile or Scrum software development methodologies; Experience with Salesforce testing (Apex, Lightning Web Components, Salesforce APIs); Familiarity with Amazon Connect or contact center platforms; Experience testing AI/ML systems and validating model outputs; Experience with AI model monitoring, A/B testing frameworks, and automated performance validation; Experience building quality gates for rapid AI deployment pipelines using enterprise automation tools; Knowledge of AI safety testing, bias detection, and automated compliance validation; Familiarity with CI/CD frameworks, processes, and tools for continuous testing and integration