PeopleofSuperintelligence

Public voice

Claire O'Brien Rajkumar

Claire O'Brien Rajkumar is an Amazon responsible-AI policy leader whose work has spanned machine-learning products and model safety. In a 2023 AWS workshop, she presented SageMaker low-code tools as a senior product manager; in April 2024, she co-authored a guide to moving workflows between SageMaker Canvas and Studio. She co-authored a January 2026 evaluation of Nova 2.0 Lite and contributed to Amazon Nova's selective-unlearning work in July 2026. As of October 2026, she leads Amazon's responsible-AI policy and product team, which works with scientists across model development and maps potential harms into model policies.

Now at
Amazon
Works
1

Publication numbers from OpenAlex, as of 15 October 2026. Citations and h-index are hidden because this OpenAlex record may be incomplete or mix in other authors.

Timeline

  1. 2023

    A SageMaker low-code workshop

    In 2023, she presents SageMaker low-code tools, including Data Wrangler, Autopilot, and JumpStart, while serving as a senior product manager at AWS.

  2. April 2024

    SageMaker Canvas and Studio

    In April 2024, she co-authors an AWS guide on moving machine-learning workflows between no-code SageMaker Canvas and code-first Studio. Her SageMaker role focuses on Canvas.

  3. January 2026

    Evaluating Nova 2.0 Lite

    In January 2026, she co-authors an evaluation of Nova 2.0 Lite under Amazon's Frontier Model Safety Framework. The report tests risks across CBRN, offensive cyber operations, and automated AI R&D.

  4. July 2026

    Selective unlearning for Nova

    In July 2026, she contributes to selective-unlearning work for Amazon Nova, which explores ways to make models forget selected behaviors.

  5. As of October 2026

    Leading responsible-AI policy

    As of October 2026, she leads Amazon's responsible-AI policy and product team. The team partners with scientists during model development, maps potential harms into behavioral policies, and implements safeguards and red-teaming.

Sources and credits

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  1. Accelerate your ML journey with Amazon SageMaker low-code ML tools pages.awscloud.com. Checked 15 October 2026.
  2. Seamlessly transition between no-code and code-first machine learning with Amazon SageMaker Canvas and Amazon SageMaker Studio aws.amazon.com. Checked 15 October 2026.
  3. Evaluating Nova 2.0 Lite model under Amazon's Frontier Model Safety Framework arxiv.org. Checked 15 October 2026.
  4. Teaching models to forget: Selective unlearning with Amazon Nova aws.amazon.com. Checked 15 October 2026.
  5. Building trust into AI amazon.science. Checked 15 October 2026.