Software Development Engineer, FBA Defect Prevention

- 3+ years of non-internship professional software development experience
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience programming with at least one software programming language
- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent

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Join a new team and make a huge difference for Amazon, our sellers, and our supply chain. We are the team that deals with the exceptions to the exceptions in a complex process, saving Amazon and our sellers many millions of dollars.

The FBA Defects Prevention team within Fulfillment By Amazon is responsible for identifying and preventing defects in the FBA Supply Chain. We work across sellers, fulfilment technology, robotics and carriers to detect, root cause, gather evidence and ultimately prevent issues in the supply chain.

As you can imagine, Amazon's inbound supply chain are incredibly complex and highly scaled. While most people marvel at the efficiency with which the inbound processes handle most shipments, we are the team that deals with the exception - when things go wrong, we're the ones engaged to root cause and identify the problems.

Examples of defects include sellers sending in the wrong item, failing to label or mislabeling packages, sending shipments to the wrong location, or failing to prep them. Detecting that these things have happened are hard - the signals coming from the network are often contradictory and misleading. We gather evidence, root cause, determine the ground truth, and then reach out to sellers to help them correct issues.

We drive projects that save Amazon between tens and hundreds of millions of dollars through prevention and resolution of these issues, and are critical path to reducing Amazon's Cost to Serve as well as ensuring seller inbound shipments are efficiently received and available to customers.

The Defect Prevention space is complex, highly scaled, and ripe for use of new technologies. We can use Gen AI to analyze patterns, assess root causes, evaluate image data, and ultimately craft the right message to communicate with sellers on what has gone wrong.

In addition, this is a problem area that is well suited to someone who is interested in deep diving complex issues, and then crafting solutions that effectively influence seller behavior.