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Security Engineering Vulnerability Protect Engineer

TEKEngineersIncUnited States🇺🇸United StatesPosted Sep 30, 2026

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
United States
Posted
18 hours ago

Job Description

Job Title: Security Engineering Vulnerability Protect Engineer
Location: Remote
Duration: Long term
End Client : Banking Domain  
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 HiddenLayer 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 HiddenLayer platform
  •     Integrate HiddenLayer 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 HiddenLayer
    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 Google Cloud Platform
  •     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
  •  

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