Job Description – AI-Driven Cybersecurity Scanning Engineer

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)

Job Overview

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.

Key Responsibilities

• 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.

Required Technical Skills

• 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

Hands-on Experience

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.

Preferred Qualifications

• 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.

Experience Requirements

• 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.