Software Development Engineer, Amazon Private Brands

Amazon Private Brands (APB) is reinventing Product Lifecycle Management (PLM) with AI at its core. Private Brands Central (PBC) is our PLM platform, and we're building a new generation of AI-native experiences, from Gen AI copilots that accelerate new product development to agentic workflows that automate the manual, high-dwell steps in bringing a product to market.

As a Software Development Engineer II on our team, you will design and build the AI-powered components and features that make this happen, working across the full software development lifecycle, from working backwards from customer needs through design, implementation, testing, deployment, and operations. This is a hands-on role where you'll embed Gen AI and agentic capabilities into sourcing, quality, sustainability, and detail-page workflows, turn functional and technical requirements into clean, maintainable code, and collaborate closely with engineers and internal customers to deliver the right solutions. You'll get to apply the latest Gen AI tools and techniques to real, high-volume product-development problems and see the efficiency gains land. Your work will directly shape how APB products are sourced, developed, and launched.

Key job responsibilities - Design and implement scalable components and features across the PBC PLM platform, translating functional and technical requirements into clean, well-structured code. - Contribute across the full software development lifecycle — design, code review, testing, deployment, and operational support — identifying and resolving root causes of operational issues. - Build customer-facing experiences and back-end services that support sourcing, quality, sustainability, and detail-page workflows. - Collaborate with engineers, product partners, APB stakeholders, and the 3P PLM vendor to understand needs and deliver the right solutions. - Evaluate and integrate new tools and approaches — including generative AI and automation capabilities — to improve productivity, code quality, and product-development workflows.

A day in the life You might start your morning reviewing a design document for a new PBC feature, then jump into a code review with a teammate before writing code for a capability that helps APB teams move faster. After lunch, you could pair with a colleague to troubleshoot an operational issue, find its root cause, and implement a permanent fix. Throughout, you'll balance new feature work with operational improvements, and regularly connect with the engineers and business partners who rely on the systems you build.

About the team This team builds functional modules within the Private Brands Central Product Lifecycle Management tool to accelerate speed to market for new product development for Amazon Private Brands (APB) and reduce dwell time for specific processes, increasingly powered by Gen AI and automation. Examples include: developing an externalized module for sourcing Request For Quotations (RFQs) from APB suppliers, launching an automated process to manage sustainability and quality related claims for APB products, and automating ASIN and Detail Page creation on Amazon systems. The team is partnering with a 3P solution to build out an integrated PLM tool with an industry-leading software solution. - 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 - Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence - 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 - Experience building complex software systems that have been successfully delivered to customers, or experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware

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