Director, AI Security Automation Engineering Bethesda, MD; Remote

Location:

Remote, Bethesda, MD

Contract Duration: 12 Months

Position Overview:

The Director will lead efforts to standardize and automate security reviews for AI systems. This role bridges security governance, engineering, and operations to create efficient, AI-assisted review processes. The ideal candidate will have a strong background in security risk assessment, AI/ML automation, and knowledge representation.

Key Responsibilities:

• Security Review Process Standardization: Develop templates for AI deployment patterns and automate control checklists.
• Throughput Engineering: Define complexity models and manage operational dashboards to track review metrics.
• AI-Assisted Assessment Automation: Implement AI-powered assessment tools and automate intake and triage pipelines.
• Pattern Graph and Knowledge Architecture: Build a queryable security pattern graph for comprehensive risk analysis.
• Control Mapping and Evidence Pipelines: Develop pipelines to connect review findings with compliance reporting.
• Governance Pipeline Optimization: Optimize the security review pipeline with AI-specific criteria and ensure EU AI Act compliance.
• Cross-Functional Coordination: Collaborate with engineering and risk teams to enhance review processes.

Qualifications:

• Education: Master's or Ph.D. in Computer Science, Cybersecurity, Information Systems, or related field.
• Experience: 10 years in complex data models or system architectures and 2 years in cybersecurity or security risk management.
• Proven experience in applying AI/ML for security and compliance automation at scale.
• Strong track record of transforming manual processes into automated, metrics-driven operations.
• Experience with knowledge graph architectures and graph-based reasoning in compliance and security domains.
• Strong communication skills to engage with senior executives and cross-functional teams.

Technical Skills:

• Deep understanding of AI system architectures and multi-agent orchestration patterns.
• Experience with graph databases and knowledge representation tools like Neo4j and Graph
  
  ML.
• Proficiency in Go and Python for building automation tools and data pipelines.
• Experience with AI/ML frameworks and security automation tools.
• Familiarity with security review frameworks and controls such as NIST AI RMF and ISO 42001.
• Experience with workflow platforms like Service Now or Jira for process automation.
• Knowledge of secure Dev Ops/MLOps pipelines and security protocols.