Security Engineer II, AWS Applied AI Solutions Security

Amazon • Seattle, WA

2d

About The Position

As part of the AWS Applied AI Solutions organization, we have a vision to
provide business applications, leveraging Amazon's unique experience and
expertise, that are used by millions of companies worldwide to manage day-to-day
operations. We will accomplish this by accelerating our customers' businesses
through delivery of intuitive and differentiated technology solutions that solve
enduring business challenges. We blend vision with curiosity and Amazon's
real-world experience to build opinionated, turnkey solutions. Where customers
prefer to buy over build, we become their trusted partner with solutions that
are no-brainers to buy and easy to use.

As an AI Security Engineer (SecEng), you will collaborate with our development
teams to ensure we keep our customers safe while developing novel AI-powered
services. The ideal candidate combines deep technical security acumen with
specialized expertise in AI/ML security and an ability to lead by influence and
communicate clearly. Technically, this person will be a security generalist with
deep expertise in AI security, including model security, adversarial ML, secure
AI development practices, and agentic AI security. In their communication, they
will clearly articulate AI-specific risks—from model poisoning to prompt
injection to data exfiltration through AI agents—to technical and non-technical
audiences alike. Interpersonally, successful candidates will effectively
harmonize disparate opinions while effectively prioritizing AI security risks to
guide their partners towards secure AI solutions.

Requirements

• 3+ years of programming in Python, Ruby, Go, Swift, Java, .Net, C++ or similar object oriented language experience
• 3+ years of scripting, programming, and security code review in a common programming language (non-internship) experience
• 2+ years of troubleshooting systems issues, analyzing logs, or automating basic tasks using command line tools (non-internship) experience
• Bachelor's degree in computer science or equivalent
• Bachelor's degree in a STEM field (Science, Technology, Engineering, Mathematics), or experience in IT Security
• Bachelor's degree in a STEM field (Science, Technology, Engineering, Mathematics), or 2+ years of IT Security experience
• Knowledge of networking protocols such as HTTP, DNS and TCP/IP
• Knowledge of industry-based security vulnerabilities and remediation techniques
• Experience in scripting, programming, and security code reviewing in a common programming language (non-internship)
• Experience in troubleshooting systems issues, analyzing logs, or automating basic tasks using command line tools (non-internship experience)

Nice To Haves

• 3+ years of any combination of the following: threat modeling experience, secure coding, identity management and authentication, software development, cryptography, system administration and network security experience
• 2+ years of scripting, programming, or security code review in a common language, such as Python, Java or C++ experience
• Knowledge of command line tools to troubleshoot protocols, analyze log outputs, or automate basic tasks
• Knowledge of system security vulnerabilities and remediation techniques, including penetration testing and the development of exploits or equivalent
• Knowledge of networking protocols, to include HTTP(S), DNS, and TCP/IP
• Experience with AWS products and services
• Experience with programming languages such as Python, Java, C++
• Experience in scripting, programming, or security code reviewing in a common language, such as Python, Java, or C++
• Experience performing security activities across one or more phases of the software development lifecycle (SDLC), such as security design review, threat modeling, secure code review, and security testing

Responsibilities

• Creating, updating, and maintaining threat models specifically for AI/ML systems, including LLMs, agentic AI platforms, model training pipelines, and AI inference services
• Security architecture and design guidance for AI systems, including secure model deployment, AI agent orchestration security, and AI supply chain security
• AI-specific secure code review for ML training pipelines, inference services, and agentic AI frameworks,
• Manual and automated secure code review for AI/ML applications and supporting infrastructure
• Application security reviews
• Secure architecture design and Threat modeling
• Projects and research work as needed development teams
• Security guidance documentation
• Security metrics delivery and improvements
• Security analysis of AI agent tool use, function calling, and external integrations
• Data privacy and security review for AI training data, including PII detection, data lineage tracking, and secure data handling in ML pipelines
• Model governance and security controls for model versioning, access control, and audit logging
• Security training and outreach for AI/ML development teams on secure AI development practices
• Independently solve AI security problems that require novel methods or approaches
• Influence your team's and partners' process, priorities, and choices to improve AI security outcomes
• Drive adoption of responsible AI practices and AI risk management frameworks

Benefits

• 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
• parental leave

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level