Applied Scientist III, AI & AGI Security

About the role

We are seeking an Applied Scientist to contribute to the research and development of novel security validation and monitoring techniques for AI systems at scale. You will own and contribute to four critical work-streams:

• Real-Time Agent Monitoring

Design and implement scientific approaches for continuous behavioral analysis of AI agents in production-detecting anomalous actions, prompt injection exploitation, and policy violations in real time.

• Protection & Automated Remediation

Invent and deliver novel protection technologies and automated remediation techniques, building on research in security, cryptography, privacy, automated reasoning, and other domains, to enable safe and secure agentic AI models and AI applications.

• AI Application and Capabilities Validation

Invent and deliver scalable methodologies for security testing of AI applications and AI capabilities (e.g. MCP, skills), including adversarial robustness evaluation, safety guardrail bypass detection, tool-use authorization boundaries, and trust boundary verification.

• AI Asset Discovery & Inventory

Research and build scalable techniques to discover, identify, and catalog automatically all AI-enabled applications, services, and capabilities across the company-maintaining a comprehensive, continuously updated database of AI assets.

Key job responsibilities

Invent

• Identify and frame new research challenges in AI security where problems are ill-defined and require novel scientific paradigms at the product level.
• Contribute to the team's scientific agenda for agent monitoring, protection, remediation, validation research, and AI asset discovery.
• Publish research results at peer-reviewed internal and external venues (e.g., USENIX Security, ACM CCS, IEEE S&P, NeurIPS, ICML security workshops, ICSE, PETS) when appropriate.
• Articulate key scientific challenges of current and future AI security threats and deliver novel research to address them.
• Design, implementation, and successful delivery of scientifically complex security solutions into production-both brand new systems and evolutions of existing ones.
• Write significant portions of critical-path code for detection models, validation engines, protection technologies, and asset discovery / classification systems.
• Assess and select appropriate technologies (e.g., data protection, private inference, graph-based anomaly detection, NLP-based service classification, code/traffic analysis for AI fingerprinting) for production systems.
• Use best practices in scientific methodology and software engineering across the team; provide insightful peer reviews of code, design, and architecture artifacts.
• Deliver solutions that are inventive, maintainable, scalable, and extensible.

Influence

• Autonomously drive discussions with security engineers, software engineers, product managers, and scientist peers across multiple teams.
• Build consensus on larger cross-team security initiatives and factor complex efforts into independent workstreams.
• Identify and resolve endemic problems, including areas where current security tooling limits innovation of partner teams.
• Contribute to the broader internal and external scientific communities as a subject matter expert in AI security.

Why Amazon Security?

At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon's products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores.

Inclusive Team Culture

In Amazon Security, it's in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices.

Training & Career Growth

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, training, and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there's nothing we can't achieve.

Basic Qualifications

• 5+ years of building machine learning models for business application experience
• PhD, or Master's degree and 6+ years of applied research experience
• Experience programming in Java, C++, Python or related language
• Experience with neural deep learning methods and machine learning

Preferred Qualifications

• Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
• Experience with large scale distributed systems such as Hadoop, Spark etc.

Additional information

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

Pay and benefits

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.

USA, NY, New York - 183,800.00 - 248,700.00 USD annually