Hebert Ntse
Cloud & AI Security Engineer | AWS | Azure | GCP | Wiz | Terraform | Python

Security controls for cloud systems and AI applications.

I build cloud remediation workflows and AI runtime guardrails that turn risky inputs, findings, and model outputs into controlled, observable security decisions.

Open to Cloud Security, AI Security, DevSecOps, and Security Automation roles.
About

Security engineering across cloud infrastructure and the AI application layer.

I build practical security workflows across AWS, Azure, GCP, Wiz, Terraform, Python, and SQL. My work turns cloud findings and AI runtime risks into repeatable controls: inspect the signal, enforce policy, route exceptions, and leave a useful audit trail.

This portfolio shows how I think as an engineer: not just identifying cloud risk, but designing systems that help teams respond faster while keeping control over production change.

Credentials

Certifications that back the cloud and AI security work.

CompTIA · CY0-001 CompTIA SecAI+

Securing AI systems, AI-assisted security operations, threat analysis, and responsible AI governance, risk, and compliance.

AWS AWS Certified Security - Specialty

Security architecture, identity, logging, monitoring, data protection, and incident response across AWS environments.

AWS AWS Certified Solutions Architect - Associate

Resilient cloud design, networking, IAM, storage, compute, and cost-aware architecture foundations.

HashiCorp HashiCorp Certified: Terraform Associate

Infrastructure as code, reusable modules, state management, secure delivery patterns, and repeatable cloud provisioning.

AI Security

Guardrails between users, models, tools, and sensitive data.

Featured Project · Google Cloud

Model Armor runtime security gateway

A reference implementation that inspects prompts before model inference and screens responses before release. Policy templates detect prompt injection, jailbreak attempts, sensitive data, malicious URLs, and unsafe content, while Cloud Logging preserves evidence for tuning and investigation.

Explore the architecture →
01User promptUntrusted input
02Model ArmorInspect and enforce
03LLMApproved inference
04Response scanPrevent data leakage
Cloud Security

Cloud automation built around controls, ownership, trust, and evidence.

Operating Model

Designed to automate clear decisions and escalate ambiguous risk.

01 Detect

Wiz controls identify cloud exposure patterns with structured context.

02 Validate

Python checks severity, ownership, resource type, account scope, and exception state.

03 Decide

Automation chooses remediate, notify, skip, or route for review based on guardrails.

04 Evidence

Every action records decision inputs, result, failure reason, and audit trail.

Open to roles Cloud Security · AI Security · DevSecOps · Security Automation
hebertntse@gmail.com