Sr. AI Security Enterprise Architect

Sr. AI Security Enterprise Architect

We're seeking a Senior AI Security Enterprise Architect to lead the design and governance of secure, scalable AI solutions for a large enterprise environment. If you're passionate about AI security, enterprise architecture, and emerging AI technologies, this is an exciting opportunity to shape the future of secure AI adoption.

The Senior AI Security Enterprise Architect role defines and governs the security architecture for AI-enabled solutions. This role blends enterprise architecture and AI security expertise to help design secure, scalable, and resilient AI capabilities; advise business and technology leaders; translate objectives into actionable roadmaps; and promote responsible, secure-by-design AI adoption.

The architect will work across applications, data, integration, infrastructure, and security domains, with emphasis on generative AI, agentic AI, AI platforms, and emerging technologies. This position develops reference architectures, standards, governance models, and reusable patterns that enable innovation while managing risk.

Enterprise Architecture Leadership

• Develop 1–3-year roadmaps that move current-state architectures toward future-state AI security capabilities.
• Partner with stakeholders to identify, architect, and govern AI security solutions aligned to business objectives.
• Own conceptual and logical architectures across application, data, integration, infrastructure, and security domains.
• Promote reuse, standardization, modernization, portfolio optimization, and technical debt reduction.
• Assess emerging technologies, industry trends, and best practices; recommend adoption strategies aligned to enterprise priorities.

AI Security Architecture

• Define and champion foundational AI security architecture across the AI lifecycle, from design through production and operations.
• Develop AI reference architectures, security patterns, guardrails, and standards for generative AI, agentic AI, machine learning, and intelligent automation.
• Establish secure-by-design principles for identity, access, data protection, model governance, API security, monitoring, and operational controls.
• Guide adoption of AI platforms and tooling, including Microsoft Copilot, Claude Code, AI agents, and emerging enterprise AI technologies.
• Partner with development, cybersecurity, infrastructure, platform engineering, and data teams to enable secure, scalable AI adoption.
• Ensure AI solutions align with security policies, regulatory requirements, risk practices, and architecture standards.
• Evaluate AI threats and emerging risks; define mitigation strategies that support resilient, auditable, and sustainable AI patterns.

Stakeholder and Vendor Engagement

• Build relationships with business leaders, technology teams, security stakeholders, and vendors.
• Serve as an AI security thought leader and evangelist for architecture practices, standards, and industry developments.
• Align enterprise standards, governance frameworks, and delivery practices with architecture teams and technology partners.
• Communicate complex recommendations clearly to executives, business partners, and technical teams.

Skills

Core Qualifications

• 10+ years of progressive experience in enterprise, solution, application, infrastructure, security architecture, or related technology roles.
• Experience developing enterprise roadmaps, target-state architectures, and cross-domain solution designs.
• Strong knowledge of application portfolios, distributed systems, cloud platforms, APIs, event-driven architecture, integration, and modern software engineering.
• Hands-on architecture experience across applications, data, infrastructure, cloud, and security domains.
• Experience with AI, machine learning, generative AI, and agentic AI in enterprise environments.
• Strong understanding of AI security, including governance, model security, prompt security, data protection, identity and access, and operational controls.
• Knowledge of security frameworks, risk management, and regulatory requirements relevant to AI adoption.
• Experience evaluating technology platforms, vendors, and emerging technologies.
• Deep understanding of SDLC, architecture methods, and enterprise architecture frameworks.
• Strong analytical, communication, stakeholder management, and influence skills.

Preferred Qualifications

• Experience in financial services, insurance, or other regulated industries.
• Experience with Microsoft Copilot, Anthropic, agent frameworks, AI gateways, vector databases, or AI governance platforms.
• Familiarity with secure AI development, AI threat modeling, model risk management, and responsible AI frameworks.
• Relevant enterprise architecture, cloud, cybersecurity, or AI certifications such as TOGAF, SABSA, CISSP, GCP Cloud Architect, or similar.

Education

• Advanced degree in Computer Science, or related discipline, or equivalent experience.
• Working knowledge of systems architectural concepts and frameworks like TOGAF preferred.
• Some previous project leadership experience is desirable. Applicable certifications preferred.