Software Dev Engineer, Alexa Connections

Amazon Amazon · Big Tech · IN, TN +1 · Software Development

Software Development Engineer role at Amazon Alexa Connections, focusing on integrating generative AI and machine learning into communication features to enhance customer experiences. The role involves designing and building scalable, fault-tolerant systems for AI/ML workloads, including Gen AI inference and training pipelines, within an agile environment.

What you'd actually do

  1. Collaborate with experienced cross-disciplinary Amazonians to conceive, design, and bring innovative products and services to market, leveraging generative AI capabilities.
  2. Design and build innovative technologies in a large distributed computing environment, integrating Gen AI models and LLMs to enhance customer experiences.
  3. Create solutions to run predictions on distributed systems with exposure to innovative technologies at incredible scale and speed, including Gen AI inference and training pipelines.
  4. Build distributed storage, index, and query systems that are scalable, fault-tolerant, low cost, and easy to manage/use, optimized for AI/ML workloads.
  5. Design and code the right solutions starting with broadly defined problems, applying Gen AI techniques where appropriate.

Skills

Required

  • 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 modern language such as Java, C++, or C# including object-oriented design

Nice to have

  • Bachelor's 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
  • Bachelor's degree or equivalent

What the JD emphasized

  • generative AI
  • machine learning
  • Gen AI models
  • LLMs
  • Gen AI inference and training pipelines
  • AI/ML workloads
  • Gen AI techniques
  • Gen AI capabilities

Other signals

  • generative AI
  • machine learning
  • LLMs
  • Gen AI inference and training pipelines
  • AI/ML workloads