Manager, Software Development, Selling Partner Selection Success

Are you passionate about leading an innovative team of engineers to build state-of-art machine learning and AI-powered solutions that help sellers succeed on Amazon? The Selling Partner Selection Success organization is looking for a Software Development Manager to lead our engineering efforts across New Selection Success and Seller Growth Recommendations. Our mission is to empower sellers to successfully launch new products, discover growth opportunities, and grow their businesses while delivering a great customer experience.

As a Software Development Manager on our team of scientists and engineers, you will have opportunities to make a significant impact on our systems, our business, and most importantly, our customers. You will lead a team working across a diverse and evolving technology stack, spanning agentic AI and large language model (LLM)-powered systems, machine learning and deep learning models. You will own the end-to-end engineering lifecycle of these solutions, from building intelligent seller-facing experiences to developing scalable ML infrastructure and MLOps capabilities that enable rapid experimentation, reliable model deployment, and efficient production operations.

You will work closely with Applied Scientists, Product Managers, and other engineering teams to translate innovative scientific solutions and ambiguous business needs into scalable, production-ready capabilities. You will drive technical vision, navigate complex engineering challenges across multiple AI/ML paradigms, and foster a culture of invention, operational excellence, and continuous improvement. This role offers a unique opportunity to shape the engineering foundation of next-generation AI-powered seller experiences while building and developing a high-performing engineering team.

Key job responsibilities

• Define and drive the engineering vision and technical strategy for AI/ML-powered solutions across New Selection Success and Seller Growth Recommendations.
• Lead the design, development, and operation of scalable seller-facing applications and services leveraging tech stacks such as agentic AI, LLMs, machine learning, and deep learning.
• Own end-to-end MLOps and AI infrastructure, including model deployment, inference serving, monitoring, and lifecycle management, and partner closely with Applied Scientists to to enable rapid experimentation and efficient delivery of new features.
• Drive engineering excellence and operational best practices to ensure the scalability, reliability, performance, and cost efficiency of production systems.
• Hire, mentor, and develop a high-performing engineering team, fostering a culture of innovation, ownership, and continuous improvement.
• Collaborate with product and business stakeholders to translate ambiguous customer needs into actionable engineering plans and deliver measurable seller and business impact.