At a Glance
- Tasks: Join the Rufus team to build scalable test automation frameworks and drive quality excellence.
- Company: Be part of Amazon's innovative Development Centre in London.
- Benefits: Competitive salary, diverse workplace, and opportunities for growth.
- Other info: Collaborative environment with a focus on diversity and inclusion.
- Why this job: Make an impact on cutting-edge AI technology while enhancing your skills.
- Qualifications: Experience in programming and building test automation frameworks.
The predicted salary is between 72000 - 88000 £ per year.
We are looking for a passionate and skilled Software Development Engineer in Test (SDET) to join the Rufus Quality Engineering team. Rufus is Amazon's conversational AI shopping assistant, and as an SDET on this team, you will play a critical role in building scalable test automation frameworks, enabling Continuous Deployment (Full CD), and driving quality excellence across Rufus services. This role is ideal for engineers who thrive at the intersection of software development and quality engineering — building tools, frameworks, and intelligent systems that empower developers to ship high‑quality features at speed.
Key job responsibilities
- Test Automation Framework Development: Design, build, and maintain scalable test automation frameworks for Rufus backend services, frontend applications, and GenAI model validation.
- Tool Development: Build and maintain internal testing tools that enable 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, model response quality benchmarking, and regression testing.
- Autonomous Test Generation: Contribute to the development of agentic AI systems for autonomous test generation, intelligent failure analysis, and predictive quality modeling.
- Collaboration: Partner with feature teams to embed quality earlier in the development lifecycle, reducing production escapes through proactive testing and quality gates.
Basic Qualifications
- Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design.
- Experience building test automation frameworks and tools.
Preferred Qualifications
- Knowledge of overall system architecture, scalability, reliability, and performance in a database environment.
- Experience with security in service-oriented architectures and web services.
Software Dev. Engineer in Test, Conversational shopping in London employer: Amazon Inc.
At Amazon Development Centre in Edinburgh, we are committed to fostering a collaborative and inclusive work culture that empowers our employees to innovate and excel. As an Applied Scientist in our Intelligent Talent Acquisition team, you will have the opportunity to work on cutting-edge machine learning technologies that directly impact recruitment processes, while benefiting from mentorship and professional growth opportunities. Join us to make a meaningful difference in how talent is acquired globally, all within a vibrant city known for its rich history and dynamic tech scene.
StudySmarter Expert Advice🤫
We think this is how you could land Software Dev. Engineer in Test, Conversational shopping in London
✨Join Local Tech Meetups
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✨Contribute to Open Source Projects
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We think you need these skills to ace Software Dev. Engineer in Test, Conversational shopping in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Amazon Inc..
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Amazon Inc. and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Amazon Inc.
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Amazon Inc. uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
