Description

Responsibilities

• Lead security reviews of solution and domain architectures, ADRs, and AI-enabled platforms.
• Assess GenAI and agentic solution designs for model security, data protection, prompt integrity, provenance, and safe orchestration of agents.
• Evaluate proposals for alignment with enterprise standards, regulatory expectations, and risk tolerance.
• Produce actionable review comments with traceable recommendations, covering both traditional and AI-driven architectures.
• Author and maintain ADRs, patterns, and reference architectures, including those covering GenAI system integration, LLM usage, and multi-agent frameworks.
• Ensure architectural documentation expresses the problem space, options, controls, and trade-offs clearly and defensibly.
• Promote structured architectural reasoning supported by both human and GenAI-assisted analysis workflows.
• Define and assess controls for GenAI systems, including model access, data boundaries, prompt injection defenses, and guardrails for AI agents performing autonomous actions.
• Evaluate the security of agent frameworks, LLM pipelines, and model-hosting platforms.
• Contribute to enterprise policy for responsible AI use and GenAI-assisted development.
• Provide domain expertise in application, cloud, and data security, augmented by AI security design considerations.
• Support teams in safely embedding GenAI copilots, RAG systems, and autonomous agents within business processes.
• Lead threat modeling for composite systems where GenAI interacts with APIs, data stores, and user environments.
• Use and refine GenAI tools for document review, security design assistance, and ADR quality assurance.
• Develop reusable prompts, review heuristics, and decision frameworks that enhance SARB throughput and consistency.
• Mentor peers in human-AI collaborative authoring, emphasizing accountability and verification of AI output.

Qualifications

• Required
  • Bachelor's or Master's degree in Computer Science, Cybersecurity, or related field.
  • 7+ years of experience in architecture or security design, including AI-related systems.
  • Demonstrable experience with secure implementation of GenAI or autonomous agents in enterprise settings.
  • Strong authorship and analytical writing skills with clear articulation of decisions and consequences.
  • Expertise in enterprise security architecture frameworks such as SABSA, TOGAF, and NIST CSF.
  • Knowledge of GenAI systems architecture, LLM lifecycle, and model governance.
  • Understanding of AI security patterns, including threat modeling for LLMs, data leakage prevention, and agent control.
  • Broad experience across cloud, data, application, and API security domains.
• Preferred
  • Certifications: CISSP, CCSP, SABSA, TOGAF, or AI-specific credentials such as NIST AI RMF, MIT AI Ethics, or Azure AI Engineer.
  • Familiarity with tools for architectural diagramming, review automation, and GenAI-assisted design such as LangChain, OpenAI GPT, and Guardrails AI

Key Skills

Education

Bachelor's or Master's degrees