Job description

We are seeking a Senior Applied Scientist to lead research and development of novel security validation and monitoring techniques for AI systems at scale. You will own and contribute to four critical workstreams: 1. 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. 2. MCP Server Validation Develop novel validation frameworks to assess the security posture of Model Context Protocol (MCP) servers, including input sanitization verification, tool-use authorization boundaries, and data exfiltration detection. 3. AI-Enabled Application Validation Invent and deliver scalable methodologies for security testing of AI-enabled applications, including adversarial robustness evaluation, safety guardrail bypass detection, and trust boundary verification. 4. AI Asset Discovery & Inventory Research and build scalable techniques to automatically discover, identify, and catalog all AI-enabled applications and services 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. • Drive the team's scientific agenda for agent monitoring, validation research, and AI asset discovery; propose new initiatives and secure leadership buy-in. • Publish research results at peer-reviewed internal and external venues (e.g., USENIX Security, IEEE S&P, NeurIPS, ICML security workshops) when appropriate. • Articulate key scientific challenges of current and future AI security threats and present interventions to address them. • Make trade-offs between short-term tactical security needs and long-term research investments. Implement • Lead the 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, and asset discovery / classification systems. • Independently assess and select appropriate technologies (e.g., streaming inference frameworks, graph-based anomaly detection, NLP-based service classification, code/traffic analysis for AI fingerprinting) for production systems. • Drive adoption of 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, product managers, and scientist peers across multiple teams. • Build consensus on larger cross-team security initiatives and factor complex efforts into independent workstreams. • Proactively identify and resolve endemic problems, including areas where current security tooling limits innovation of partner teams. • Actively recruit, mentor, and develop other scientists; provide technical assessments for promotions. • Contribute to the broader internal and external scientific communities as a subject matter expert in AI security. About the team Diverse Experiences Amazon Security values diverse experiences. Even if you do not meet all of the 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. 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. - PhD, or Master's degree and 5+ years of applied research experience - Experience programming in Java, C++, Python or related language - 5+ years of building machine learning models for business application experience - Experience with neural deep learning methods and machine learning - 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. 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 amazon.jobs for more information. If the country/region you’re applying in isn’t 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 amazon.jobs . USA, NY, New York - 183,800.00 - 248,700.00 USD annually

Requirements

Must-haves

We are seeking a Senior Applied Scientist to lead research and development of novel security validation and monitoring techniques for AI systems at scale. You will own and contribute to four critical workstreams:
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.
MCP Server Validation
Develop novel validation frameworks to assess the security posture of Model Context Protocol (MCP) servers, including input sanitization verification, tool-use authorization boundaries, and data exfiltration detection.
AI-Enabled Application Validation
Invent and deliver scalable methodologies for security testing of AI-enabled applications, including adversarial robustness evaluation, safety guardrail bypass detection, and trust boundary verification.
AI Asset Discovery & Inventory
Research and build scalable techniques to automatically discover, identify, and catalog all AI-enabled applications and services across the company—maintaining a comprehensive, continuously updated database of AI assets.
Key job responsibilities
Identify and frame new research challenges in AI security where problems are ill-defined and require novel scientific paradigms at the product level.
Drive the team's scientific agenda for agent monitoring, validation research, and AI asset discovery; propose new initiatives and secure leadership buy-in.
Publish research results at peer-reviewed internal and external venues (e.g., USENIX Security, IEEE S&P, NeurIPS, ICML security workshops) when appropriate.
Articulate key scientific challenges of current and future AI security threats and present interventions to address them.
Make trade-offs between short-term tactical security needs and long-term research investments.
Lead the 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, and asset discovery / classification systems.
Drive adoption of 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.
Autonomously drive discussions with security engineers, product managers, and scientist peers across multiple teams.
Build consensus on larger cross-team security initiatives and factor complex efforts into independent workstreams.
Proactively identify and resolve endemic problems, including areas where current security tooling limits innovation of partner teams.
Actively recruit, mentor, and develop other scientists; provide technical assessments for promotions.
Contribute to the broader internal and external scientific communities as a subject matter expert in AI security.

Nice-to-haves

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Application prep

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Keywords to mirror

aijavapythonmachine learning

Platform: amazon
Effort: medium

Benefits

Benefits detected in the listing.

Health Insurance

Dental

Vision

401(K)

Paid Time Off

Parental Leave