About Luis E. Ramirez
I work where application security, AI security governance, and agentic engineering meet. My focus is helping teams turn ambiguous AI/product risk into clear architecture, bounded automation, reusable evidence, and controls that engineers can actually operate.
Working thesis
I am strongest in environments where the security function is still being formed: the controls are not all mapped, the AI workflows are still fluid, and the organization needs someone who can define what good looks like without slowing engineering to a crawl.
I combine manual security judgment with automation that stays bounded, reviewable, and evidence-backed. Repeated work such as questionnaires, vulnerability routing, AI control mapping, and evidence collection should become a reusable system with human accountability at the final decision point.
I fit teams building high-trust software: SaaS platforms, AI-enabled workflows, regulated products, and organizations that need practical security leadership before they have a large formal security department.
Strengths
Background
Advises early-stage and growth organizations on application security, AI systems security, compliance readiness, agentic workflow design, and practical control implementation.
Built Webflow's initial AppSec function, integrated security tooling into developer workflows, and partnered on secure design review for product and GenAI feature work.
Reviewed Python services and ML platform workflows, threat modeled AI/ML product features, and supported cloud migration security work.
Delivered hands-on security assessments across web, mobile, infrastructure, cloud, and application environments for enterprise clients.
Contact
Available for focused security leadership, advisory, and implementation work.
