Sde, Responsible AI

Amazon Amazon · Big Tech · Seattle, WA · Software Development

Software Development Engineer to build a platform for AI governance at Amazon, ensuring AI systems are fair, safe, transparent, and compliant with regulations. The role involves designing and building systems for discovering, classifying, and monitoring AI workloads, collaborating with scientists on AI-powered classification agents, and ensuring operational excellence for regulatory reporting.

What you'd actually do

  1. Design, develop, and operate distributed services that automatically discover and catalog AI systems across Amazon's infrastructure
  2. Build classification and risk-assessment pipelines that map AI systems to regulatory frameworks and internal compliance requirements
  3. Develop self-service tooling and paved-path integrations that help builder teams demonstrate conformance with responsible AI expectations
  4. Build the infrastructure that hosts and scales ML-powered compliance workflows developed by our Applied Science team
  5. Partner with Privacy, Legal, and RAI Science to translate evolving regulatory requirements into scalable technical solutions

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
  • 1+ 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
  • 1+ years of Object Oriented Design experience

Nice to have

  • 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
  • Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference lifecycles, and optimization techniques
  • Experience developing using AI tooling such as Claude Code, Kiro, or Cursor

What the JD emphasized

  • building from scratch
  • greenfield opportunity
  • define the technical direction
  • AI governance at this scale

Other signals

  • building the platform that gives Amazon real-time visibility into the compliance posture of thousands of AI systems
  • automating what would take an army of auditors
  • design and build systems that discover AI workloads across Amazon's fleet, classify them against regulatory risk frameworks, streamline compliance evidence collection through paved-path tooling, and surface actionable insights
  • collaborate closely with Applied Scientists developing AI-powered classification agents