Enterprise Architect
Indexed description
Full-time
Charlotte
Responsibilities:
Enterprise AI Architecture:
- Define and maintain enterprise architecture across application, data, integration, cloud, and platform domains
- Establish architecture principles, standards, and reference architectures
- Ensure consistent adoption of enterprise patterns across technology initiatives
- Integrate AI, automation, and analytics capabilities into the broader enterprise architecture
- Align technology architecture with business strategy and long-term roadmap
Technical Leadership:
- Provide architectural leadership across major enterprise initiatives
- Guide solution architects and engineering teams on architecture decisions
- Define reusable architectural patterns and shared platform capabilities
- Act as a design authority for complex, cross-domain solutions
- Balance innovation with stability, security, and operational maturity
Standards & Governance:
- Establish governance models for platforms, integrations, data, and AI-enabled solutions
- Define security, compliance, and risk guardrails in collaboration with security and risk teams
- Review solution designs for alignment with enterprise standards
- Ensure architectural consistency across cloud, SaaS, and on-prem solutions
- Promote observability, resiliency, and operational readiness by design
Solution Design & Review:
- Review and approve AI solution designs
- Ensure alignment with enterprise architecture standards
- Identify opportunities for reusable components
- Guide teams on technical implementation approaches
- Evaluate new AI technologies and platforms
Platform Evolution:
- Drive the evolution of Citco's AI platform capabilities
- Identify and evaluate emerging AI technologies
- Define roadmap for platform capabilities and features
- Guide integration with existing enterprise systems
Requirements:
- 10+ years of experience in enterprise or solution architecture roles
- Strong background in large-scale, distributed enterprise systems
- Proven experience designing cloud-native and hybrid architectures
- Hands-on understanding of data, integration, and platform architectures
- Experience incorporating AI and automation into enterprise solutions (not limited to AI platforms)
- Enterprise architecture frameworks, principles, and governance
- Application, data, integration, and cloud architecture
- Strong understanding of security, compliance, and risk considerations
- Cloud platforms (AWS, Azure, or equivalent)
- API-driven and event-driven architectures
- Data architecture, governance, and integration patterns
- Ability to translate strategy into executable architecture
- Clear technical communication with senior stakeholders
- Large Language Models and GenAI technologies
- RAG architectures and implementation patterns
- Cloud AI services (AWS, Azure, GCP)
- Enterprise integration patterns
- Security and compliance frameworks
- Data architecture and governance
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