Software Development Engineer II, Fulfillment Optimization, SCOT Fulfillment Optimization - Luxembourg | Amazon Job

Job Description

Join the Fulfillment Optimization (FO) organization within SCOT, where we improve customer experience and reduce cost by designing the fulfillment network, orchestrating resource planning, and optimizing order fulfillment at massive scale. As an SDE I on our team, you'll build and operate systems that directly impact how millions of packages reach customers — quickly, efficiently, and reliably.

Key job responsibilities
- Work on Tier 1 production services that power fulfillment at Amazon scale
- Build resiliency, stress testing, and chaos engineering capabilities for critical fulfillment systems
- Operate at the intersection of software engineering and supply chain optimization
- Collaborate with scientists, PMs, and engineers solving complex network-level optimization problems
- Develop, test, and deploy software components for fulfillment optimization systems using a native AWS stack
- Participate in on-call rotations and drive operational excellence for team-owned services
- Write clean, testable, and well-documented code

Basic Qualifications:

- Experience designing or architecting (design patterns, reliability and scaling) of new and existing systems
- Experience building complex software systems that have been successfully delivered to customers
- Experience debugging, profiling, and implementing best software engineering practices in large-scale systems
- Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design

Preferred Qualifications:

- Bachelor's degree in computer science or equivalent
- Experience with full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
- Experience in machine learning, data mining, information retrieval, statistics or natural language processing
- Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution
- Experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems

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