Senior Software Dev Engineer, Product Quality Tech

- 5+ years of non-internship professional software development experience
- 5+ years of programming with at least one software programming language experience
- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience as a mentor, tech lead or leading an engineering team
- Master's degree in computer science or equivalent
- Working experience with launching ML and LLM solutions and collaborating with ML scientists

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $151,300/year in our lowest geographic market up to $261,500/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
We protect customers from unsafe, counterfeit, damaged, and otherwise unsavory products offered by 3rd party sellers on the Amazon website. We want you to help us evolve our systems to better recognize and prevent these products from reaching our customers. The trust of our customers and sellers is of paramount importance, and we will continue to ensure that Amazon is the best place in the world to buy and sell products.


Key job responsibilities
We work on a multi-tenant Large Language Model (LLM) application infrastructure backed by AWS Bedrock, as a GenAI foundational capability, to provide easiest way to build applications leveraging generative AI and protect customer trust at Amazon.

We work on very large scale systems, evaluating millions of sellers and billions of listings. We need to continuously improve our ability to recognize and take action against before these offers are presented to customers, or as quickly as possible once they let us know there is a problem. We are also constantly enhancing our systems to ensure we are not negatively impacting good sellers, and providing self-service mechanisms to reinstate listings that were taken down in error.

We also provide tools for our external customers such as sellers and our internal stakeholders to get detailed views of enforcement actions, provide feedback to improve the accuracy of our models, and track performance of our programs so they can target new approaches to thwart bad actors.

A day in the life
SDEs at Amazon are owners, and will work closely with business stakeholders to drive the correct solutions to the problems facing our buyers and sellers. They will help establish requirements, generate designs, implement large systems, and own and improve these systems after launch. They will also support their teammates in providing thoughtful reviews of designs and code to keep the quality bar high.

About the team
Our team owns tools for external customers such as sellers and internal stakeholders such as investigators to collect and visualize necessary data and solve difficult product quality issues. We use many machine learning technologies such as image processing, deep learning, and similarity search to automatically process customer invoices, package label images, x-ray images, and etc. Our team is rapidly growing with plentiful career growth opportunities.