SDE-T , Ring/Blink CS Technology Enablement

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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.

Key job responsibilities
Key job responsibilities

The successful Software Development Test Engineer will be obsessed with customer experience and quality improvement.

In this role, you will:



Code Development & Delivery

Write secure, stable, testable, maintainable code that consistently meets high quality standards

Apply best practices in all aspects of software development and testing



Test Automation & Framework Development



Design, develop, and execute comprehensive test automation frameworks using AccelQ and Amazon internal test automation tools for web applications, APIs, and integrated systems

Build scalable test automation solutions for Salesforce Lightning components, Amazon Connect flows, AI services, and AWS service integrations

Use technology to validate and verify software, seeking input from team members on the best software test techniques to utilize

Develop custom testing tools and utilities that enable the team to efficiently validate complex AI-powered workflows

Create reusable test libraries and patterns that accelerate test development across the organization

Establish automated validation pipelines for AI model outputs, conversation flows, and intent recognition accuracy



Quality Transformation & Process Improvement



Dive deep into testing methodologies to transform manual quality processes into highly automated quality solutions, specifically targeting AI validation bottlenecks

Improve your team's automation of development, testing, and deployment processes using Amazon's internal testing ecosystem

Design, develop, and execute automation test plans and reporting on test execution

Coordinate test approaches, test cases, and test methodology with remote teams

Drive continuous improvement in test coverage from current 65% to target 90%, with focus on AI-critical paths

Transform manual AI testing processes into highly automated, reliable quality gates

Integration & End-to-End Testing

Own the end-to-end testing strategy across Salesforce, Amazon Connect, AI services, and AWS platforms

Design and execute integration test suites that validate data flow and business logic across system boundaries

Implement API testing frameworks for RESTful services and AWS service integrations

Validate AI model outputs and ensure quality of AI-powered customer service features

Automate the validation of modern user interfaces and cloud infrastructures

Build automated testing for conversational AI flows, including edge cases and error scenarios

Performance & Security Testing



Conduct performance testing and capacity planning for high-traffic customer service applications and AI services

Implement load testing strategies to validate system behavior under peak conditions, including AI service performance

Implement security testing practices and validate compliance with Amazon security standards

Establish performance benchmarks and regression testing for critical user journeys

Create performance testing frameworks for AI services under varying load conditions

Team Collaboration & Mentorship



Communicate technical concepts and processes using clear, simple language and visuals

Collaborate with development teams to shift testing left and implement test-driven development practices

Work in Agile/Scrum development methodologies with cross-functional teams

Collaborate with AI/ML teams to implement test-driven AI development practices

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