Amazon Senior Security Data Scientist Global Services 

United States, Kansas 

145607956

This role with partner with the existing Security Experts to validate that security controls are enabled throughout the lifecycle of traditional Machine Learning and Generative AI phases of model development. The security controls will be defined from the early experimentation phases to model fine-tuning to model deployment and ongoing operational governance.
Key job responsibilities
• Lead the development of security guidance on the use of AI/ML, particularly generative AI
• Collaborate with security experts to validate and recommend security controls applicable for all phases of AI/ML/Gen AI development lifecycle
• Design, build, test, and help deploy ML and generative AI solutions that have measurable business and customer impact in security.
• Interact with internal and external customers to understand their business problems and help them in implementation of their generative AI and ML solutions
• Facilitate discussions with senior leadership regarding technical / architectural trade-offs, best practices, and risk mitigation
• Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder
• Create detailed security documentation of solutions using reference architectures and implementation/configuration guidance
• Collaborate with AI/ML peers to research, design, develop, and evaluate cutting-edge generative AI algorithms to address real-world challenges
• Provide customer and market feedback to Service and Engineering teams to help define product direction
• Work with a cross section of AI experts to develop solutions that will be piloted with customers for their production workloads
About the team
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
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We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Hybrid Work

- Bachelor's degree in computer science, engineering, mathematics or equivalent
- Experience building models with deep learning frameworks like MXNet, Tensorflow, Keras, Caffe, PyTorch, or similar
- 5+ years of relevant experience in developing and evaluating deep learning models and/or systems, including batch and real-time data processing
- Experience with two or more of prompt engineering, retrieval-augmented generation (RAG), vector databases, or LLM frameworks such as Hugging Face, Langchain or LlamaIndex.
- 3+ years of experience in security architecture or engineering including application security, secure SDLC, or cloud security