SDET: GenAI & Test Automation for Conversational AI

Owen Thomas B Corp; Greater London; Hybrid; GBP 70,000 - 100,000; Full time

Job summary

Amazon's Rufus Quality Engineering team seeks a passionate Software Development Engineer in Test (SDET) to join the conversational AI shopping assistant Rufus. You will build scalable test automation frameworks for backend services, frontend apps, and GenAI model validation.

This role blends software development with quality engineering, creating tools and intelligent systems that empower developers to ship high-quality features quickly while reducing production issues.

Qualifications

• Experience programming in a modern language (Java, C++, or C#) with object-oriented design.
• Experience building test automation frameworks and tools.

Responsibilities

• Test Automation Framework Development: design, build, and maintain scalable test automation frameworks for backend services, frontend apps, and GenAI model validation.
• Tool Development: build and maintain internal testing tools enabling SDEs to self-serve test execution and quality validation.
• GenAI Quality Validation: develop testing strategies and tooling for validating generative AI outputs, including prompt engineering evaluation and regression testing.
• Autonomous Test Generation: contribute to AI systems for autonomous test generation, intelligent failure analysis, and predictive quality modelling.
• Collaboration: partner with feature teams to embed quality earlier in the development lifecycle and reduce production issues.

Skills

Java

C++

C#

Test automation

Job description

Amazon's Rufus Quality Engineering team seeks a passionate Software Development Engineer in Test (SDET) to join the conversational AI shopping assistant Rufus. You will build scalable test automation frameworks for backend services, frontend apps, and GenAI model validation.

This role blends software development with quality engineering, creating tools and intelligent systems that empower developers to ship high-quality features quickly while reducing production issues.