Security Architect

We are looking for a Security Architect with thorough technical knowledge and strong hands-on experience in designing and implementing security solutions. Criterion Enterprise security review / tiger team Application Security (AppSec) SaaS Security Network Security (NetSec) Cloud architecture security reviews Architecture Decision Records (ADRs) AI; API; AWS; Cryptography; DB Architecture & Design; Git (GitHub, GitLab, BitBucket, SVN); Machine Learning; Azure; Big Data; eCP; GCP; Palo Alto; Postgres / Postgresql; ServiceNow Job Title: Security Architect – • Architecture Review, GenAI & Governance Role Summary • The Security Architect will be part of a team whose role is to assure enterprise security architecture with a focus on the review and authorship of Architecture Decision Records (ADRs) and Security Architecture Review Board (SARB) submissions. • The role blends deep technical acumen with emerging expertise in Generative AI (GenAI)and Agentic systems, ensuring secure design, governance, and responsible adoption of intelligent automation within the enterprise. Key Responsibilities • Architecture Review & Advisory 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. • Authoring & Governance 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. • GenAI & Agentic Security Define and assess controls for GenAI systems, including Model access, data boundary, and prompt injection defences. • Guardrails for AI agents performing autonomous actions or multi-step reasoning. • Secure orchestration, isolation, and human oversight mechanisms. • Evaluate the security of agent frameworks, LLM pipelines, and model-hosting platforms (e.g., Vertex AI, Azure OpenAI). • Contribute to enterprise policy for responsible AI use and GenAI-assisted development. • Technical Leadership 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. • Continuous Improvement & Automation 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. • Core Competencies Enterprise security architecture (SABSA, TOGAF, NIST CSF). • GenAI systems architecture, LLM lifecycle, and model governance. • AI security patterns (threat modeling for LLMs, data leakage prevention, agent control).Strong authorship and analytical writing—clear articulation of decisions and consequences. • Familiarity with tools for architectural diagramming, review automation, and GenAI-assisted design (e.g., LangChain, OpenAI GPT, Guardrails AI). • Broad experience across cloud, data, application, and API security domains. Qualifications Bachelor’s or master’s in computer science, Cybersecurity, or related field. • 7+ years of experience in architecture or security design, including AI-related systems. • Desirable certifications: CISSP, CCSP, SABSA, TOGAF, or AI-specific credentials (e.g., NIST AI RMF, MIT AI Ethics, Azure AI Engineer). • Demonstrable experience with secure implementation of GenAI or autonomous agents in enterprise settings. • Success Measures Secure-by-design adoption of GenAI and agentic capabilities across business domains. • Clear, complete, and AI-assisted ADRs produced and reviewed efficiently. • Reduced residual security risk in AI and non-AI solutions through proactive architectural engagement. • Recognition as a thought leader in secure GenAI architecture and governance.