AI Solution Architect
Role details
Job location
Tech stack
Job description
Client is seeking one (1) Senior Solution Architecture Lead to serve as the principal architect for enterprise technology initiatives focused on Artificial Intelligence, Data Warehousing, Cloud Platforms, Advanced Analytics, and Enterprise Integration. The consultant will lead multiple concurrent technical initiatives of integrating AI capabilities to data warehouse platforms, oversee end to end solution architecture, and ensure all technology implementations align with Client enterprise architecture standards, AI policies, security policies, and business objectives. The candidate shall have advanced expertise in AI technologies, data warehouse, cloud platforms, data engineering, machine learning, and integration best practices, and will act as a trusted technical advisor to technical teams, business partners, and Executive leadership., * Lead enterprise architecture for AI/ML, cloud, analytics, and data warehouse solutions.
- Design and implement Generative AI and LLM-enabled solutions.
- Architect scalable, secure, cloud-native applications and integrations.
- Lead data warehouse, ETL, data modeling, and governance initiatives.
- Develop architecture standards, design patterns, and technical documentation.
- Review and approve solution designs, integration patterns, and architectural artifacts.
- Mentor technical teams and provide architecture leadership.
- Ensure compliance with enterprise architecture and cybersecurity standards.
Support production issue resolution and technical strategy.
Requirements
- 10+ years of enterprise architecture, data warehouse architecture, and advanced analytics experience.
- 3+ years designing architectures that integrate Generative AI into BI/Data Warehouse environments.
- 5+ years of cloud architecture experience (AWS, Azure, or Google Cloud Platform).
- Experience with Terraform or Infrastructure-as-Code.
- 5+ years leading cross-functional technical teams.
- 5+ years designing enterprise integrations using APIs, microservices, event-driven architectures, and data integration technologies.