Sr. Software Development Engineer, Shopping; Rufus

Position: Sr. Software Development Engineer, Amazon Shopping (Rufus)
Description

We're enhancing the shopping experience on Amazon through the conversational capabilities of large language models, and we're looking for innovative professionals who are passionate about technology and customer experience. You'll have the opportunity to contribute meaningfully to the industry while working alongside talented scientists, engineers, and technical program managers (TPMs) to create solutions that serve our customers.

If you're excited about collaborating with a dynamic team and contributing to this evolving field, we'd love to have you join us on this journey!

Key job responsibilities

We're looking for an experienced Software Development Engineer with expertise in back-end system and online service to architect, design, and develop agentic services and applications powered by large language model.

In this role, you will build expertise in online service architecture, API development, and distributed systems that power responsive agentic AI applications 'll get opportunities to develop service orchestration patterns, efficient agent frameworks, and real-time processing systems, partnering with engineers and scientists in a fast-paced environment to deliver exceptional user experiences. You'll also contribute to our technical roadmap, service reliability metrics, and optimizations focused on building intelligent agents that can effectively reason, plan, and execute complex tasks on behalf of users.

In this role, you'll help establish best practices that improve LLM application efficiency, enable new agentic AI features for Stores customers with LLM capabilities.

You'll work with your team to design, implement large scale distributed agentic AI applications at scale, partnering with technical and business leaders in a collaborative environment to create value for our customers. You'll also contribute to prioritization, estimation, and sprint planning activities.

About the team

The charter of the Amazon Shopping Team is to improve shopping on Amazon using the conversational capabilities of large language models. We are working on an AI-first initiative to further improve the way we do search using large-scale foundation models. These foundation models are also used in downstream applications by various partner teams in Amazon Stores. Our goal is to build large language models (LLMs), which can empower conversational applications and facilitate online shopping.

Basic Qualifications

- 5+ years of non-internship professional software development experience

- 5+ years of programming with at least one software programming language experience

- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience

- Experience as a mentor, tech lead or leading an engineering team

- Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference life cycles, and optimization techniques

Preferred Qualifications

- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience

- Experience building or operating LLM-powered agent systems (tool use, ReAct loops, multi-step orchestration)

- Experience with agent evaluation frameworks - offline evaluation, LLM-as-Judge, composite scoring, or quality measurement at scale.

- Experience hosting or serving large language models at scale (model deployment, inference optimization, GPU cluster management, vLLM/Tensor

RT)

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Los Angeles County applicants:
Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material…