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Remote role, strong startup brand, and mid-level generalist security title increase applicant competition.
Security and cloud skills transfer across industries, but AI-integrated AppSec requires specialized experience.
Explicit 4-6 years, hands-on AI, and deep AWS/AppSec requirements raise filtering strictness.
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Develop and own AI-powered security automation including vulnerability triage, automated code security reviews, and incident forensics at scale.
Build and manage cloud security automation systems for AWS (primary), GCP, and Azure addressing configuration drift, IAM issues, and exposed secrets with end-to-end ownership.
Lead application security efforts including threat modeling, security reviews, risk assessments and embed security tools into CI/CD pipelines for developer workflow integration.
4-6 years experience in cloud-native SaaS environments, preferably with expertise in both Application Security and Cloud Security.
Hands-on experience integrating large language models (LLMs) or AI into production security workflows.
Deep practical AWS expertise including IAM, VPCs, and Kubernetes security.
Work Experience Required: 4-6 years in relevant cloud-native SaaS security roles.
Operator who drives end-to-end security solutions from identifying vulnerabilities through building fixes to closing the loop independently.
Experienced in cloud security and application security within high-growth or product startup environments.
Pragmatic AI practitioner applying AI/LLMs for scalable security automation and developer-embedded security tools.