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Senior, specialized principal role at a recognized metro enterprise reduces applicant density.
Requires cross-product enterprise AI and data architecture experience, limiting transferability across industries.
Explicit 10+ years and mandatory AI, data platform, cloud skills enforce strict filters.
Set and govern data architecture direction across multiple product lines including warehouses, lakehouses, graphs, and vector stores supporting analytics and AI.
Define reference architectures and standards for applied AI systems (e.g., RAG, agentic AI, LLM integration) with governance and safety considerations.
Act as a technical authority consulted by architects and engineering teams; represent data and AI architecture perspectives in review boards and cross-product standards discussions.
10+ years experience in software architecture, data engineering, or AI/ML systems.
Bachelor's degree in Computer Science or equivalent professional experience.
Demonstrated design and delivery of production-scale data architectures using layered patterns (e.g., medallion/bronze-silver-gold).
Hands-on experience architecting production applied AI systems (e.g., RAG pipelines, LLM services) and building cloud-native applications on AWS, Azure, or GCP with Kubernetes.
Experienced in cross-product or cross-organization architecture roles within large enterprise software companies.
Broad knowledge across data warehousing, lakehouses, data platforms, graphs, and vector technologies rather than deep specialization.
Familiarity with data contract/product standards (ODCS, ODPS), metadata management tools, agentic AI architectures, interoperability protocols (MCP, A2A), and AI safety patterns for governance and compliance.