Software Dev Engineer, Agentic Ai, Agentic AI Foundation

Amazon Amazon · Big Tech · NY +1 · Software Development

Software Development Engineer role focused on building a new AWS service for agentic AI, specifically enabling memory capabilities for autonomous agents. The role involves designing, developing, and deploying large-scale, fault-tolerant ML systems, collaborating with applied scientists, and mentoring junior engineers.

What you'd actually do

  1. build a new AWS service that is going to be trend setting in the Gen AI field
  2. deliver large scalable systems, design new software systems and have a significant bottom-line impact on our business and competitive position
  3. draw from a deep and broad technical expertise to mentor engineers and provide leadership on complex technical issues
  4. designing, developing, testing, and deploying distributed machine learning systems and large-scale solutions for our world-wide customer base
  5. collaborate closely with a team of applied scientists to influence our overall strategy

Skills

Required

  • 3+ years of non-internship professional software development experience
  • 3+ years of programming with at least one software programming language experience
  • 3+ years of contributing to new and current systems architecture and design (architecture, design patterns, reliability and scaling) experience

Nice to have

  • Experience with machine learning systems is preferred
  • 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

What the JD emphasized

  • hard engineering challenges
  • tier zero Amazon service
  • scalable, efficient, and fault tolerant
  • large scale software systems
  • fast moving, startup environment in a large company

Other signals

  • building a new AWS service
  • enabling both short and long term memory capabilities of agentic systems
  • designing, developing, testing, and deploying distributed machine learning systems