Cloud Security (Vulnerability) - Remote Role

Job Title: Security Engineering Vulnerability Protect Engineer

Location: Remote

Duration: 6+ Months

Responsibilities

Security Engineering Vulnerability Protect Engineer

About the Role We're seeking an experienced Security Engineering Vulnerability Protect Engineer to lead the deployment, administration, and strategic use of the Hidden Layer platform in defense of our AI/ML systems. This role sits at the intersection of cybersecurity engineering and applied machine learning, focused on protecting models and LLM-based applications from adversarial attacks, data poisoning, model theft, and other emerging AI-specific threats. You'll partner closely with Data Science, MLOps, and broader security teams to build a resilient, well-governed AI security posture across the organization.

Responsibilities Platform Operations

Deploy, configure, and administer the Hidden Layer platform

Integrate Hidden Layer with enterprise SIEM, SOAR, EDR, vulnerability management, and cloud security platforms

Create detection rules, dashboards, and executive reporting on AI security posture

AI/ML Threat Protection

Protect AI models against adversarial attacks, model theft, prompt injection, model poisoning, and unauthorized inference

Develop monitoring and detection strategies for production AI workloads

Conduct AI threat modeling exercises

Respond to AI-related security incidents and perform root cause analysis

Security Assessment & Governance

Assess AI applications for security risks across the full development lifecycle

Design governance around AI model inventory, risk classification, and lifecycle management

Document architecture, standards, and operational procedures

Cross-Functional Partnership

Partner with Data Science and MLOps teams to implement secure model deployment pipelines

Stay current on emerging AI attack techniques and defensive capabilities Required Qualifications

5+ years of experience in cybersecurity engineering or security architecture

2+ years supporting AI/ML security initiatives

Hands-on experience deploying or administering Hidden Layer

Working knowledge of adversarial machine learning techniques, including:

Prompt injection

Model extraction

Data poisoning

Model evasion

Membership inference

Supply chain attacks

Experience securing LLM-based applications

Understanding of AI model lifecycle management

Familiarity with Python and REST APIs

Experience with Kubernetes and container security

Knowledge of AI services on AWS, Azure, or GCP

Experience integrating security platforms via APIs and automation Preferred Qualifications

Experience with additional AI security platforms: Protect AI, Microsoft AI Security, NVIDIA AI Enterprise Security, or Palo Alto AI Runtime Security

Experience with ML platforms/tools: MLflow, Kubeflow, SageMaker, Vertex AI, or Azure Machine Learning

Experience with SIEM platforms: Splunk, Microsoft Sentinel, Google Chronicle, or QRadar

Security certifications: CISSP, GSEC, GIAC, or cloud security certifications

Familiarity with AI governance frameworks: NIST AI Risk Management Framework, OWASP Top 10 for LLM Applications, or MITRE ATLAS