Software Development Manager, Amazon Product Catalog, Contribution and Item Pipelines

Want to make the Earth"s largest product catalog of billions of items, available in any language, all over the world, all the time, in milliseconds, millions of times per second?

The catalog team is looking for a highly technical, AI-native leader who wants to be at the absolute frontier of applied AI and ship it at planetary scale. You and your team of engineers will take a well-established catalog orchestration platform and reinvent it as an AI-first system, one where LLMs and autonomous agents own ever-larger parts of the loop to enrich, validate, and self-heal the catalog in real time. You"ll pioneer agentic workflows, model-driven orchestration, and human-in-the-loop guardrails to tackle some of the hardest architectural problems in the industry: reliability, latency, and trust at Amazon"s scale. This is a rare opportunity to set the technical strategy for how AI reshapes commerce itself. You"ll power Amazon"s expansion into new countries, languages, physical stores, and product lines, and define what the catalog becomes in an agent-driven world.

Your breadth of impact will range from how sellers and vendors list their products with Amazon"s catalog, to how products move through Amazon"s fulfillment centers and to how our shopping customers find and discover the products they love!

As an SDM, you are empowered to:

• Own the technical vision, strategy, planning, and prioritization for evolving the catalog orchestration platform - driving architectural decisions and end-to-end delivery as the system adapts to new classes of workloads.
• Identify, assess, and mitigate risks - provide escalation management, anticipate tradeoffs, and balance business needs against technical constraints.
• Create, maintain, and disseminate project information to stakeholders; drive alignment across engineering, science, and product teams.
• Manage and grow a team of talented engineers - making great hiring decisions, setting goals, providing feedback, and managing performance.
• Develop best practices to build and operate critical catalog platform services that handle both traditional low-latency workloads and ML-powered processing at scale.