Software Dev Engineer II

Amazon Amazon · Big Tech · IN, TS, Hyderabad · Software Development

Software Development Engineer II at Amazon, focused on building the platform for designing and managing Amazon's global transportation network. The role involves calculating capacity, predicting gaps, identifying at-risk packages, and responding to real-time disruptions. It utilizes AWS services, big data processing (Spark/Scala), optimization algorithms, machine learning models, and GenAI. The position requires operating at all levels, providing strategic inputs, driving planning and execution, and contributing to talent development and operational excellence.

What you'd actually do

  1. As a leader on the team, you will be expected to operate at all levels, diving deep into the details while providing strategic inputs for the product.
  2. You will be a key player in driving strategic planning, project execution, hiring and development of engineering talent, driving operational excellence, and shaping up the solutions to achieve our vision.
  3. We build the platform that transportation teams use to design and change the network - from evaluating new lanes to putting them live.
  4. We calculate how much capacity each node and lane will have, so the network can handle the volume.
  5. We identify where capacity will fall short and alert operators before it becomes a problem.

Skills

Required

  • 3+ years of non-internship professional software development experience
  • 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
  • Experience programming with at least one software programming language

Nice to have

  • 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
  • Bachelor's degree in computer science or equivalent

What the JD emphasized

  • modeling capacity across a massive global network
  • managing thousands of network changes safely
  • predicting capacity gaps weeks in advance
  • detecting and responding to disruptions in real-time
  • keeping systems running 24/7

Other signals

  • machine learning models
  • GenAI
  • optimization algorithms