Job Summary

Must-Have Skills

• Experience: 7+ years in enterprise architecture or security design, including experience with AI-related systems.
• Security architecture: Strong enterprise security architecture expertise across application, cloud, data, and API security domains.
• Architecture review: Proven ability to review solution and domain architectures, Architecture Decision Records (ADRs), and Security Architecture Review Board (SARB) submissions.
• Architecture authorship: Ability to author and maintain ADRs, security patterns, and reference architectures that clearly document the problem, options, controls, trade-offs, decisions, and consequences.
• GenAI and agentic security: Deep understanding of GenAI architectures, LLM lifecycles, agentic systems, multi-agent frameworks, and model governance.
• AI security controls: Practical knowledge of model access controls, data boundaries, data leakage prevention, prompt-injection defenses, prompt integrity, provenance, agent guardrails, secure orchestration, isolation, and human oversight.
• Threat modelling: Ability to lead threat modelling for composite solutions in which GenAI interacts with APIs, data stores, applications, and user environments.
• Enterprise AI implementation: Demonstrable experience securing enterprise GenAI solutions or autonomous agents, including copilots, retrieval-augmented generation systems, LLM pipelines, and model-hosting platforms.
• Governance and risk: Ability to evaluate designs against enterprise standards, regulatory expectations, responsible-AI principles, and organizational risk tolerance.
• Architecture frameworks: Working knowledge of SABSA, TOGAF, and NIST Cybersecurity Framework principles.
• Technical writing and communication: Strong analytical writing, stakeholder communication, and the ability to produce clear, traceable, actionable security recommendations.
• Leadership: Ability to advise delivery teams, mentor peers, promote accountable human-AI collaboration, and verify AI-generated output.
• Education: Bachelor’s or Master’s degree in Computer Science, Cybersecurity, or a related field.

Key Responsibilities

Must-Have Skills

• Experience: 7+ years in enterprise architecture or security design, including experience with AI-related systems.
• Security architecture: Strong enterprise security architecture expertise across application, cloud, data, and API security domains.
• Architecture review: Proven ability to review solution and domain architectures, Architecture Decision Records (ADRs), and Security Architecture Review Board (SARB) submissions.
• Architecture authorship: Ability to author and maintain ADRs, security patterns, and reference architectures that clearly document the problem, options, controls, trade-offs, decisions, and consequences.
• GenAI and agentic security: Deep understanding of GenAI architectures, LLM lifecycles, agentic systems, multi-agent frameworks, and model governance.
• AI security controls: Practical knowledge of model access controls, data boundaries, data leakage prevention, prompt-injection defenses, prompt integrity, provenance, agent guardrails, secure orchestration, isolation, and human oversight.
• Threat modelling: Ability to lead threat modelling for composite solutions in which GenAI interacts with APIs, data stores, applications, and user environments.
• Enterprise AI implementation: Demonstrable experience securing enterprise GenAI solutions or autonomous agents, including copilots, retrieval-augmented generation systems, LLM pipelines, and model-hosting platforms.
• Governance and risk: Ability to evaluate designs against enterprise standards, regulatory expectations, responsible-AI principles, and organizational risk tolerance.
• Architecture frameworks: Working knowledge of SABSA, TOGAF, and NIST Cybersecurity Framework principles.
• Technical writing and communication: Strong analytical writing, stakeholder communication, and the ability to produce clear, traceable, actionable security recommendations.
• Leadership: Ability to advise delivery teams, mentor peers, promote accountable human-AI collaboration, and verify AI-generated output.
• Education: Bachelor’s or Master’s degree in Computer Science, Cybersecurity, or a related field.

Skill Requirements

Security Architect – Must-Have and Nice-to-Have Skills

Must-Have Skills

• Experience: 7+ years in enterprise architecture or security design, including experience with AI-related systems.
• Security architecture: Strong enterprise security architecture expertise across application, cloud, data, and API security domains.
• Architecture review: Proven ability to review solution and domain architectures, Architecture Decision Records (ADRs), and Security Architecture Review Board (SARB) submissions.
• Architecture authorship: Ability to author and maintain ADRs, security patterns, and reference architectures that clearly document the problem, options, controls, trade-offs, decisions, and consequences.
• GenAI and agentic security: Deep understanding of GenAI architectures, LLM lifecycles, agentic systems, multi-agent frameworks, and model governance.
• AI security controls: Practical knowledge of model access controls, data boundaries, data leakage prevention, prompt-injection defenses, prompt integrity, provenance, agent guardrails, secure orchestration, isolation, and human oversight.
• Threat modelling: Ability to lead threat modelling for composite solutions in which GenAI interacts with APIs, data stores, applications, and user environments.
• Enterprise AI implementation: Demonstrable experience securing enterprise GenAI solutions or autonomous agents, including copilots, retrieval-augmented generation systems, LLM pipelines, and model-hosting platforms.
• Governance and risk: Ability to evaluate designs against enterprise standards, regulatory expectations, responsible-AI principles, and organizational risk tolerance.
• Architecture frameworks: Working knowledge of SABSA, TOGAF, and NIST Cybersecurity Framework principles.
• Technical writing and communication: Strong analytical writing, stakeholder communication, and the ability to produce clear, traceable, actionable security recommendations.
• Leadership: Ability to advise delivery teams, mentor peers, promote accountable human-AI collaboration, and verify AI-generated output.
• Education: Bachelor’s or Master’s degree in Computer Science, Cybersecurity, or a related field.

Nice-to-Have Skills

• Cloud AI platforms: Hands-on familiarity with platforms such as Vertex AI and Azure OpenAI.
• GenAI development and guardrail tools: Experience with LangChain, OpenAI GPT, Guardrails AI, or comparable orchestration and control frameworks.
• AI-assisted architecture workflows: Experience using GenAI for document review, security-design assistance, ADR quality assurance, reusable prompt development, review heuristics, and decision frameworks.
• Architecture tooling: Familiarity with architectural diagramming, review automation, and GenAI-assisted design tools.
• Responsible-AI policy: Experience contributing to enterprise policy for responsible AI use and GenAI-assisted software development.
• Certifications: CISSP, CCSP, SABSA, TOGAF, or relevant AI credentials such as NIST AI RMF, MIT AI Ethics, or Azure AI Engineer.
• Thought leadership: Evidence of driving secure-by-design adoption, improving architecture-review throughput, reducing residual risk, or establishing reusable GenAI security practices.

Other Requirements

AI; API; AWS; Azure; Cryptography; DB Architecture & Design; GCP; Git (GitHub, GitLab, BitBucket, SVN); Machine Learning; Palo Alto; Postgres / Postgresql; Postman; Python