The Merchandising Tech team builds the technology that helps customers discover new, popular, and relevant products across Amazon worldwide. We are building the next generation of AI-driven systems that improve how millions of customers discover products across Amazon’s shopping experiences. By combining large language models (LLMs), vision-language models (VLMs), and Amazon’s first-party data on shopper behavior and conversion patterns, we design systems that assist in generating, selecting, and optimizing marketing and merchandising experiences at scale. We train, evaluate, and operate models end-to-end in-house, from data pipelines to model lifecycle management and large-scale inference, ensuring that AI capabilities are tightly integrated into our distributed systems and measurable in customer and business impact.
We are looking for a Senior Software Engineer who will lead the design and evolution of systems that generate, assemble, and optimize creative assets at scale across regions and business surfaces. You will build systems that automatically produce and adapt images, text, layouts, and multimodal content used across merchandising surfaces. These systems must balance creative flexibility, brand constraints, performance signals, and operational reliability. These platforms support high-traffic global events across Amazon marketplaces worldwide, requiring predictable scalability and operational resilience under peak conditions.
As a Senior Software Engineer, you are a recognized technical leader who drives the engineering strategy, mentors team members, and partners with cross-functional teams to deliver complex end-to-end AI solutions. Your work focuses on architecting and implementing robust systems in ambiguous problem areas where both the business problem and solution approach need to be defined. This role requires end-to-end ownership across model integration, distributed services, and measurement frameworks. You will identify structural bottlenecks in AI system evolution and design architectural boundaries that allow model development, experimentation, and application services to evolve independently without compromising reliability or scalability.
You will define architectural patterns for creative automation, establish engineering standards for AI-driven asset generation, and ensure that experimentation, ranking integration, and monitoring are designed as first-class system capabilities. You will collaborate closely with applied scientists, product managers, and downstream platform teams to translate model capabilities into reliable, scalable creative services used globally. This role offers the opportunity to take cross-organizational technical ownership, drive highly visible initiatives, and influence how GenAI systems are designed and adopted across multiple teams.
Key job responsibilities As a member of our software engineering team you can expect to:
- Solve problems which require novel solutions in low-latency systems
- Solve problems that center around scale, across all realms, over hundreds of millions of customers
- Write high quality, maintainable code
- Perform peer code-reviews and contribute to technical designs
- Integrate and collaborate with applied science experts specialized in machine learning recommendation models
- Think outside the box when it comes to innovating for the customer. Our team is looking for fresh ideas to engage with customers across both internal and external mediums
- Learn and grow from a talented group of individuals within our team and within our sister teams
- Mentor new members as we continue to add to our footprint and scope
Basic Qualifications
- Experience as a mentor, tech lead or leading an engineering team
- Experience leading the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems
- Experience in professional, non-internship software development
- Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design
- Experience in development in the last 3 years
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
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