3+ years in security engineering, cloud engineering, or ML engineering, with direct hands-on exposure to AI/ML or LLM-based systems.
Proficiency in Python and experience with ML/LLM frameworks (e.g., LangChain, Hugging Face, TensorFlow/PyTorch) or AI security tooling (e.g., guardrail frameworks, model scanning tools).
Working knowledge of cloud platforms (Azure and/or AWS/GCP) and cloud-native security controls (IAM, network segmentation, key/secrets management).
Familiarity with AI-specific threat models: prompt injection, model inversion, data poisoning, insecure output handling, excessive agency (OWASP Top 10 for LLM Applications).
Experience with CI/CD pipelines, infrastructure-as-code, and integrating security tooling into automated pipelines.
Preferred Qualifications
Experience with SIEM/SOAR platforms (Splunk, Sentinel, etc.) and scripting integrations.
Security certifications (Security+, GCIH, OSCP) or cloud certifications (AWS/Azure Security). • Prior retail or PCI-regulated environment experience.
Numbers & Facts
Location
FL
Skills
Amazon Web Services (AWS)unmatched
Artificial Intelligence (AI)unmatched
Cloud Computingunmatched
CompTIA Security+unmatched
Continuous Deployment/Deliveryunmatched
Continuous Integrationunmatched
Data Modelingunmatched
GCIH - GIAC Certified Incident Handlerunmatched
GCP (Good Clinical Practices)unmatched
Injectionsunmatched
Machine Toolunmatched
Microsoft Windows Azureunmatched
PCIunmatched
Python Programming/Scripting Languageunmatched
Retailunmatched
Scripting (Scripting Languages)unmatched
Security Information and Event Management (SIEM)unmatched
Software Engineeringunmatched
Splunkunmatched
Threat Modelingunmatched
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