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Amazon Software Development Engineer III Annapurna Labs 
United States, New York, New York 
790408479

Today
DESCRIPTION


About AWS Utility Computing (UC):
About AWS
About AWS Neuron:
You will join a dynamic team building and applying AI agents to simplify and accelerate customer adoption of Trainium and Inferentia. As a Sr. SDE you will work with external and internal customers to identify the main obstacles and the opportunities to accelerate their adoption of the Neuron technology.Key job responsibilities
- Solve challenging technical problems, often ones not solved before, at every layer of the stack.
- Design, implement, test, deploy and maintain innovative software solutions to transform service performance, durability, cost, and security.
- Build high-quality, highly available, always-on products.
A day in the life
As you design and code solutions to help our team drive efficiencies in software architecture, you’ll create metrics, implement automation and other improvements, and resolve the root cause of software defects. You’ll also:
- Participate in design discussions, code review, and communicate with internal and external stakeholders.- Work in a startup-like development environment, where you’re always working on the most important stuff.

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
- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Experience as a mentor, tech lead or leading an engineering team
- Hands-on technical experience working on the Generative AI space


PREFERRED QUALIFICATIONS

- Master's degree in computer science or equivalent
- 1+ years in machine learning or other computational modeling environments with an emphasis on building and optimizing models for diverse hardware platforms