Software Engineer

- 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
- Experience building complex software systems that have been successfully delivered to customers
- Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design
- Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution
- Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference lifecycles, and optimization techniques
- 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 in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware

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Amazon Customer Service handles hundreds of millions of customer contacts each year across every Amazon business. Our Associate Experience organization owns the products, platforms, and AI systems that determine how Customer Service Associates (CSAs) onboard, learn, receive coaching, improve performance, and collaborate with AI to deliver exceptional customer outcomes.

As Customer Service evolves, associates will increasingly solve sophisticated customer problems while AI automates routine interactions. This requires fundamentally reimagining how Amazon develops, supports, and continuously improves one of the world’s largest workforces.

We are seeking a Software Engineer with experience in Machine Learning lifecycle including data preparation, training, evaluation, and inference optimization to define and build the Associate Context & Insights platform, creating a continuously evolving representation of associates from signals across the associate lifecycle and making that context reusable across CS products.

This SDE will work with other senior engineers to define the architecture for the Associate Context & Insights platform, and own the system end to end from design, implementation, testing, and deployment. The current platform does not exist in the form it needs to, providing a rare opportunity to define an entirely new product space.

This is a highly strategic role requiring close partnership with Engineering, Science, Business Intelligence, UX, Operations, Routing, Workforce Planning, and senior leaders across Customer Service.

Key job responsibilities
> Define the long-term architecture for Associate Context & Insights platform
> Guide the team on building scalable Machine Learning Models
> Establish engineering excellence standards for the team
> Deliver the minimum viable product incrementally
> Influence senior leadership on long-term investments that improve associate capability, customer outcomes, and operational efficiency.
> Partner closely with Engineering, Applied Science, and Business Intelligence to continuously improve the product