Job Title: AI-Driven Cybersecurity Scanning Engineer
Location: Fort Collins, Colorado, USA (Remote candidates are also acceptable)
Employment Type: Contract
Experience: 4–6 Years (Role-level requirement; advanced technical experience as specified below)
We are looking for an experienced AI-Driven Cybersecurity Scanning Engineer with expertise in securing AI platforms, Large Language Models (LLMs), Generative AI agents, and Model Context Protocol (MCP) environments.
The ideal candidate will have hands-on experience in AI security, adversarial testing, cloud security, MLOps security, and DevSecOps. The candidate should be capable of identifying and mitigating security vulnerabilities in AI-driven applications, implementing security guardrails, and securing multi-agent architectures.
Design and implement AI security guardrails, safety classifiers, and security controls for GenAI applications.
Perform adversarial testing, penetration testing, and red-team assessments of LLMs and AI agents.
Evaluate AI security risks using OWASP Agentic Top 10, OWASP LLM Top 10, and MITRE ATLAS frameworks.
Implement security controls for AI/ML pipelines and MLOps environments.
Ensure model provenance, model integrity, and training-data integrity.
Implement identity and access management using SPIFFE/SPIRE.
Configure policy-based authorization using Open Policy Agent (OPA).
Establish trust and security controls across multi-agent AI architectures.
Secure MCP servers, AI integrations, and agent communication workflows.
Integrate security testing and vulnerability scanning into CI/CD pipelines.
Collaborate with AI/ML, cloud, and DevSecOps teams to strengthen overall security posture.
AI Security and Generative AI Security
Large Language Models (LLMs) and GenAI Agents
Model Context Protocol (MCP)
AI Security Guardrails and Safety Classifiers
Adversarial Testing and AI Red Teaming
OWASP LLM Top 10 and OWASP Agentic Top 10
MITRE ATLAS Framework
MLOps Security
Model Provenance and Training-Data Integrity
SPIFFE/SPIRE Identity Management
Open Policy Agent (OPA)
Multi-Agent Security and Trust Controls
Cloud Security and DevSecOps
Secure SDLC and CI/CD Security Integration
Candidates should ideally have practical experience in:
Building and securing Generative AI agents.
Implementing and securing MCP servers.
Deploying and tuning open-weight AI models.
Using cybersecurity tools for common security functions.
Identifying and mitigating vulnerabilities in AI-powered applications.
Implementing security controls across AI platforms and cloud environments.
AWS Security Specialty certification or equivalent cloud security certification.
CISSP or CCSP certification.
Experience with enterprise AI security platforms and LLM security assessments.
Knowledge of emerging AI security standards and threat frameworks.
Note: Certifications are preferred, not mandatory.
Overall experience: 4–6 years as specified for the position.
Advanced AI/GenAI and cybersecurity experience should align with the technical requirements.
Hands-on implementation experience is preferred over theoretical knowledge.
