Applied Scientist Ii- Recruiting AI Agents, Recruiting Agents & Candidate Voice

Amazon Amazon · Big Tech · Seattle, WA · Applied Science

The Applied Scientist II will design, implement, and deploy AI-powered agentic solutions for Amazon's recruiting process. This role involves creating conversational AI agents using LLMs and GenAI, developing evaluation frameworks, and collaborating with cross-functional teams to integrate these solutions into candidate-facing platforms. The position also requires staying current with agentic AI research and contributing to the scientific community.

What you'd actually do

  1. Design and architect AI-powered agentic solutions that help candidates navigate Amazon's hiring process, including scoping requirements, identifying dependencies and constraints, and creating robust scientific and technical designs that balance candidate experience with system scalability.
  2. Implement and deploy conversational AI agents leveraging state-of-the-art LLM and GenAI technologies to enable candidates to explore job opportunities, understand role requirements, and receive personalized guidance throughout their hiring journey.
  3. Develop rigorous evaluation frameworks to measure agent effectiveness, candidate satisfaction, and hiring outcomes—continuously iterating on models to improve accuracy, fairness, and user experience across millions of candidate interactions.
  4. Collaborate cross-functionally with Research Scientists, Software Engineers, and Product teams to integrate agentic solutions into Amazon's candidate-facing platforms, ensuring seamless deployment and alignment with broader Talent Acquisition goals.
  5. Drive innovation in agentic AI research by staying current with advances in NLP, LLMs, and autonomous agent architectures, while contributing to the scientific community through publications, internal tech talks, and knowledge sharing.

Skills

Required

  • building models for business application
  • PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
  • Experience programming in Java, C++, Python or related language
  • Experience in investigating, designing, prototyping, and delivering new and innovative system solutions

Nice to have

  • Experience applying theoretical models in an applied environment
  • Experience in professional software development
  • Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning

What the JD emphasized

  • AI-powered agentic solutions
  • conversational AI agents
  • agentic solutions
  • agentic AI research

Other signals

  • design and architect AI-powered agentic solutions
  • implement and deploy conversational AI agents
  • develop rigorous evaluation frameworks to measure agent effectiveness
  • drive innovation in agentic AI research