Expert Consultant- Software Engineer, Agi - Data Services

Amazon Amazon · Big Tech · Boston, MA · Software Development

This role focuses on overseeing and optimizing human-in-the-loop and model-in-the-loop data pipelines for AI solutions, ensuring data quality and providing mentorship. It involves collaborating with AI teams on data collection for LLM training and evaluating AI systems.

What you'd actually do

  1. Serve as a trusted domain advisor to cross-functional teams, providing strategic direction and specialized problem-solving support
  2. Champion domain knowledge sharing across multiple channels and teams to maintain data quality excellence and standardization
  3. Drive collaborative efforts with science teams to optimize output of complex data collections in your domain expertise, ensuring data excellence through iterative feedback loops
  4. Foster team excellence through mentorship and motivation of peers and junior team members
  5. Collaborate with AI teams to innovate model-in-the-loop and human-in-the-loop approaches, to ensure the collection of high-quality data, safeguarding data privacy and security for LLM training, and more.

Skills

Required

  • 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
  • Bachelor's degree or above in computer science or equivalent
  • Experience working with or evaluating AI systems
  • Experience guiding and coaching other developers

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
  • Experience with Cloud platforms (preferably AWS), database systems (SQL and NoSQL), AI tools for development productivity, contributing to open-source projects, and/or version control systems
  • Prior experience in defining and creating benchmarks for assessing GenAI model performance
  • Excellent written and verbal communication skills, with the ability to explain complex concepts clearly

What the JD emphasized

  • Experience working with or evaluating AI systems
  • Prior experience in defining and creating benchmarks for assessing GenAI model performance

Other signals

  • human-in-the-loop
  • model-in-the-loop
  • data pipelines
  • data quality
  • LLM training