AI Security Scientist: Code & Cloud Defense

Amazon Inc.; Austin (TX); On-site; USD 143,000 - 193,000; Full time

Benefits offered by this job

RSUs

Health insurance

401(k) matching

Job summary

Amazon Inc. is seeking an Applied Scientist to join the AI Security team. You will research, design, and implement ML and agentic systems that reason over source code, infrastructure, and security context, collaborating to improve detection, remediation quality, and coverage across Amazon.

You will lead experiments, build evaluation datasets, and apply LLMs, program analysis, and security knowledge to deliver validated findings and actionable fixes for builders across Amazon’s software estate.

Qualifications

• 3+ years of building models for business application experience.
• PhD, or Master’s 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.

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.

Skills

ML modeling

Applied ML research

Programming: Java/C++/Python

Data mining

High-performance computing

Education

PhD

Master’s + 4+ years CS/CE/ML

Tools

Unix/Linux

Professional software development

Job description

Amazon Inc. is seeking an Applied Scientist to join the AI Security team. You will research, design, and implement ML and agentic systems that reason over source code, infrastructure, and security context, collaborating to improve detection, remediation quality, and coverage across Amazon.

You will lead experiments, build evaluation datasets, and apply LLMs, program analysis, and security knowledge to deliver validated findings and actionable fixes for builders across Amazon’s software estate.