AI Security Is an Engineering Problem — How to Solve It at Every Layer of the Agent Stack
AI security isn't a policy problem—it's an engineering one. Here's how to build defensible agents at scale.
Why it matters
As agents move into production, security can't be bolted on as an afterthought. This piece articulates a framework for security-by-design across the agent stack—defining requirements, controls, and ownership patterns that practitioners need to adopt now.
The key facts
11 to knowFramed as engineering problem, not policy
Calls for defined security requirements and enforceable controls
Emphasizes named owners and evidence of protection effectiveness
Advocates for accelerating security engineering as agent capability grows
Urges industry to share defensive patterns faster
Multi-layer agent stack security approach
Security framed as engineering discipline, not infosec add-on
Emphasis on defined requirements, enforceable controls, and named owners
Multi-layer agent stack security architecture
Call for broader access to defensive tools and shared defensive knowledge
Published by NVIDIA (vendor perspective, not independent research)
Go to the source
NVIDIA Blogblogs.nvidia.com
Publisher excerpt: AI security is an engineering problem. That means defined security requirements, enforceable controls, named owners and evidence that protections work. As AI becomes more capable, the industry must accelerate security engineering, broaden access to defensive tools and share what works faster.…