Security Architect

This is a 6-month contract role based in Dallas, Texas, offering the opportunity to architect and operationalize AI cybersecurity threat monitoring capabilities. Working in a hybrid capacity (2-3 days on-site with travel as needed), you will establish threat response functions that integrate AI security into existing SOC, IR, and threat hunting workflows, using industry frameworks such as MITRE ATLAS, NIST AI RMF, and OWASP Top 10 for LLM Applications.

Responsibilities

• Define and pilot an AI Threat Modeling capability; build a comprehensive library of AI attack scenarios mapped to the MITRE ATLAS framework to support Purple Teaming and Adversary Emulation.
• Design, build, test, and tune high-fidelity AI detection rules, correlation logic, and automated response playbooks within enterprise SIEM/SOAR platforms.
• Build proactive, AI-focused threat hunting playbooks and execute targeted hunts across enterprise GenAI platforms, cloud environments, and AI APIs.
• Define telemetry, logging, and observability requirements across AI systems (including token usage, prompt/response telemetry, and MCP integrations); lead gap analyses to expand SOC visibility.
• Partner with Threat Informed Defense and Purple Teams to validate AI-specific attack paths, test defense effectiveness, and tune alerting thresholds.
• Collaborate with the IR team to author and refine AI-specific runbooks, investigation workflows, and digital forensics/evidence-gathering standards.
• Conduct organizational readiness assessments, track emerging AI attack vectors, and present risk mitigation roadmaps and investment recommendations to technology leadership.

Qualifications

• Required

• Deep background in SOC monitoring, detection engineering, SIEM/SOAR rule creation, alerting pipelines, and threat hunting workflows.

• Hands-on experience securing Generative AI, Agentic AI, Large Language Models (LLMs), Model Context Protocol (MCP), and AI APIs-especially within AWS cloud environments.

• Practical application of MITRE ATLAS, OWASP for LLM Applications, and NIST AI RMF for threat modeling and control mapping.

• Experience designing and testing attack scenarios against AI workloads to validate defensive controls.

• Proven ability to architect logging, telemetry pipelines, and data visibility requirements for cloud and AI/ML workloads.

• Understanding of security best practices for AI service accounts, automated agents, API tokens, and machine-to-machine integrations.

• Experience driving security architecture reviews, leading executive briefings, and translating complex AI risks into business decisions.

• Bachelor's degree in Cybersecurity, Computer Science, Information Systems, Data Science, Engineering, or equivalent practical experience.

• Preferred

• Advanced degree in a related field.

• CISSP, CCSP, GIAC (e.g., GDSA, GCIA, GCIH), or AWS Certified Security - Specialty.

• Advanced in AI Risk (AAIR), Advanced in AI Security Management (AAISM), CompTIA Security AI+, or equivalent specialized training.

• AWS Certified AI Practitioner or AWS Certified Cloud Practitioner.

Core Competencies

• Strong analytical mindset to parse complex telemetry and detect subtle, novel adversary techniques.
• Executive-level communication skills to present roadmaps, project health, and threat intelligence to directors, vice presidents, and engineering peers.
• Collaborative and adaptable approach in fast-moving Agile environments with shifting enterprise priorities.