Software Development Engineer, Alexa AI Logistics for Infrastructure, Cost, & Efficiency

Are you passionate about building infrastructure that powers AI at scale Do you want to work on systems that serve millions of Alexa customers every day The Alexa AI Logistics for Infrastructure Cost and Efficiency (ALICE) team is looking for Software Development Engineers to join our new India team and help build and operate Alexas LLM inference infrastructure.

At ALICE we build products and solutions that enable Alexa service owners to analyze forecast and manage infrastructure drivers costs and usage. You will be part of a founding team in India working on high-visibility high-impact systems that are critical to the success of Alexas next generation of AI experiences.

Key job responsibilities
- Design build and maintain components of the Alexas LLM Inference Service and other ALICE portfolio services leveraging GenAI at all phases of the development cycle
- Collaborate with senior engineers and the SDM to deliver features from design through production deployment
- Participate in on-call rotations and contribute to the operational excellence of Tier-1 production services
- Write clean testable maintainable code and participate actively in code reviews
- Work closely with partner teams across Alexa to deliver cross-functional projects
- Research and identify opportunities to improve service performance reliability and cost efficiency

- 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
- 3 years of designing and developing large-scale multi-tiered multi-threaded embedded or distributed software applications tools systems and services using: C# C Java or Perl experience

- Bachelors degree in computer science or equivalent
- 3 years of full software development life cycle including coding standards code reviews source control management build processes testing and operations experience
- Experience in developing and deploying LLMs in production on GPUs Neuron TPU or other AI acceleration hardware

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