Director, Threat Modeling

NorthAB LLC•Remote work MI, MI

1d•Remote

About The Position

This leadership role drives the strategic vision and technical execution of the security engineering function. The focus of this role is on implementing and optimizing advanced, automated security solutions, specifically leveraging AI, Machine Learning and algorithms for improved threat detection, log management, and incident response orchestration (SOAR). This director will manage the full lifecycle of internal security software, integrate security into cloud and CI/CD pipelines through cross-functional collaboration, and establish metrics to demonstrate the program's efficiency and return on investment.

Requirements

Bachelor's degree in Software Engineering, Computer Science, Information Technology, or a related field, or equivalent practical experience (10+ years of experience in Cybersecurity).
Strong background in cybersecurity domains including: Incident Response; Digital Forensics; Cybersecurity Program Management.
Experience conducting hunts or incident response across networks, endpoints, cloud and application environments.
Practical experience in developing agentic cybersecurity solutions.
Proficiency in leading the end-to-end lifecycle of security software and automated workflows.
Strategic vision for enterprise vulnerability management, including the ability to identify systemic workflow gaps.
Competence in digital forensics and the ability to coordinate high-fidelity security tabletop exercises.
Strong knowledge of all aspects of large-scale incident response management.
Knowledge of the MITRE ATT&CK framework and the Cyber Kill Chain. Ability to map disparate events to specific tactics, techniques, and procedures (TTPs).
Knowledge of cybercrime and nation state attack vectors, detection and mitigation strategies.
Strong technical background in security tooling and detection engineering principles (agentic solutions, detection algorithms, machine learning).
Attention to details and focus on tactical execution.

Responsibilities

Define and execute enterprise strategies for Log Management, SIEM, and AI-driven automation, ensuring architectures support scalable data ingestion, real-time threat detection, and alignment with business objectives.
Lead the end-to-end lifecycle (from design to deployment) of automated workflows, SOAR playbooks, and response scripts to streamline threat detection and maximize operational efficiency.
Own the strategic vision and day-to-day execution of the enterprise vulnerability management program.
Identify systemic workflow gaps and bottlenecks across IT operations to proactively address potential vulnerabilities before they can be exploited.
Design and execute a holistic strategy to detect, investigate, and mitigate malicious, negligent, or compromised insider activities.
Act as an internal incubator for the broader cybersecurity organization, helping cybersecurity teams identify, experiment with, and adopt cutting-edge models, algorithms, and disruptive architectural approaches.
Research and deploy innovative detection techniques, machine learning models, and predictive analytics to uncover sophisticated techniques that evade traditional rule-based and signature-based tools.
Partner with cybersecurity teams to infuse advanced automation and data-science mindsets into daily workflows, constantly pushing the boundaries of how the enterprise hunts, detects and contains threats.
Oversee the testing, validation, and continuous tuning of security controls, utilizing AI/ML and advanced analytics to reduce false positives, enhance detection accuracy, and optimize system performance.
Drive cross-functional collaboration with DevOps and IT teams to embed security automation best practices into CI/CD pipelines, cloud environments, and enterprise infrastructure.
Design, coordinate, and facilitate regular, high-fidelity security tabletop exercises for both technical teams and executive leadership.
Establish and track Key Performance Indicators (KPIs) and operational metrics to quantify program efficacy, demonstrate ROI, and drive data-informed continuous improvement.