Principal Scientist, Generative & Agentic AI Lead

Amazon Web Services (AWS); New York (NY); On-site; USD 219,000 - 296,000; Full time

Job summary

Amazon Web Services (AWS) is seeking a Principal Applied Scientist to join the Quick Science team. You will lead research and development in generative AI and Agentic AI to enable intelligent agents that perform complex reasoning, automate multi‑step workflows, and improve productivity across enterprise systems.

This role combines scientific leadership with hands‑on experimentation and close collaboration with engineering teams to bring cutting-edge research into production at scale across

Qualifications

• PhD in ML/CS/EE or a related field, or a Master’s with 5+ years of relevant experience.
• Industry experience developing ML models for real-world applications.
• Experience with generative AI, including model training or building systems with pre-trained foundation models.
• Proven record of peer-reviewed publications or granted patents in AI/ML.
• Proficiency in Python or similar programming languages.
• Experience in NLP, large language models (LLMs), computer vision, or Agentic AI.

Responsibilities

• Lead research and development efforts in generative AI and Agentic AI to enable intelligent agents for complex reasoning, multi-step workflows, and enterprise productivity.
• Build and optimize multi-modal foundation models and train/fine-tune state-of-the-art LLMs.
• Architect scalable systems that span domains and collaborate closely with engineering teams to transition research into production.

Skills

Python proficiency

Generative AI/LLMs

Research leadership

Cross-functional collaboration

Publications or patents in AI/ML

Education

PhD in ML/CS/EE or related field

Master’s with 5+ years of experience

Job description

Amazon Web Services (AWS) is seeking a Principal Applied Scientist to join the Quick Science team. You will lead research and development in generative AI and Agentic AI to enable intelligent agents that perform complex reasoning, automate multi‑step workflows, and improve productivity across enterprise systems.

This role combines scientific leadership with hands‑on experimentation and close collaboration with engineering teams to bring cutting-edge research into production at scale across