Applied Scientist, AI Security

We are seeking an Applied Scientist to join our AI Security team which builds AI-based security analysis services that identify validate and help remediate vulnerabilities in Amazon source code and cloud configurations. The team combines large language models security knowledge code analysis and security-engineer feedback to help builder teams detect security issues earlier in development and maintain security coverage across Amazon.

As an Applied Scientist you will research model design and implement machine learning and agentic systems that reason over source code infrastructure and security context. You will collaborate with applied scientists security engineers software engineers internal partners and external researchers to improve finding precision severity assessment remediation quality and continuous scanning coverage. Your work will enable continuous AI-driven security analysis across Amazons software estate converting source-code and infrastructure signals into validated prioritized findings and proposed fixes that help builders prevent security defects from reaching production.

Key job responsibilities
Research and develop accurate and scalable methods to solve our hardest AI security problems
Lead cross-functional work with applied scientists software engineers and security engineers to develop models and technical designs for AI systems that analyze source code validate security findings and generate remediation guidance at Amazon scale.


About the team
As an Applied Scientist on the AI Security team you will research develop evaluate and productionize models that identify security vulnerabilities in source code and cloud configurations. You will design experiments build evaluation datasets and metrics and apply large language models program analysis and security knowledge to improve finding precision severity assessment and remediation quality. You will work with applied scientists security engineers and software engineers to deliver systems that convert security signals into validated prioritized findings and proposed fixes for builder teams across Amazon.

Your work will shape how Amazon identifies and addresses security defects throughout the software development lifecycle. You will investigate model behavior analyze failure modes develop methods to improve recall and precision and measure the impact of new capabilities before deployment. The role provides opportunities to solve applied machine learning problems across source code infrastructure cloud services and security operations.

About the team

The AI Security team develops systems that analyze source code and cloud configurations to identify validate and help remediate security vulnerabilities. We combine large language models security engineering automated evaluation and feedback from builders and security engineers to improve security coverage across Amazon. The team works on problems including vulnerability detection severity assessment false-positive reduction remediation generation continuous scanning and security-data analysis.

Diverse Experiences

Amazon Security values varied professional and life experiences. We encourage candidates from traditional and nontraditional career paths including candidates early in their careers and candidates with alternative technical backgrounds to apply.

Why Amazon Security

Security is central to customer trust and Amazons products and services. Our organization establishes and maintains security standards across Amazon. Team members build experience across cloud devices retail entertainment healthcare operations and physical stores.

Inclusive Team Culture

Amazon Security brings together people with different experiences technical backgrounds and perspectives. We invest in learning opportunities and create space for teams to examine security problems from multiple viewpoints.

Training and Career Growth

The team provides knowledge-sharing technical training mentorship and opportunities to work across security domains. Applied Scientists can deepen their expertise in machine learning security research evaluation systems and production AI services.

Work/Life Balance

We support work-life harmony and flexible working practices. Teams plan work with sustainable delivery in mind and support employees in meeting responsibilities at work and at home.

- 3 years of building models for business application experience
- PhD or Masters degree and 4 years of CS CE ML or related field experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java C Python or related language
- Experience in any of the following areas: algorithms and data structures parsing numerical optimization data mining parallel and distributed computing high-performance computing

- Experience using Unix/Linux
- Experience in professional software development

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience qualifications and location. Amazon also offers comprehensive benefits including health insurance (medical dental vision prescription Basic Life & AD&D insurance and option for Supplemental life plans EAP Mental Health Support Medical Advice Line Flexible Spending Accounts Adoption and Surrogacy Reimbursement coverage) 401(k) matching paid time off and parental leave. Learn more about our benefits at TX Austin - 142800.00 - 193200.00 USD annually