Quantiphi is an award-winning, AI-First digital engineering and consulting company focused on delivering high-impact Services and Solutions. The role involves leading the vision for a next-generation data layer designed for Agentic AI, including system architecture, schema design, and strategic client engagement.
Responsibilities:
- Design the end-to-end blueprint for a modern data layer that seamlessly integrates structured, unstructured, and relational (Graph) data for AI agents
- Define multi-tenant schemas and Knowledge Graph ontologies that allow LLM agents to perform complex reasoning and cross-domain data retrieval
- Oversee the health, security, and performance optimization of our data clusters (Snowflake/Kinetica), ensuring 99.9% availability for mission-critical AI workflows
- Act as the "Face of Engineering" for the customer. Lead discovery workshops, manage technical expectations, and align the architectural roadmap with their business objectives
- Establish benchmarks for data latency and retrieval accuracy, ensuring the data layer can keep pace with the real-time demands of agentic execution
Requirements:
- Proven expertise in architecting for Snowflake (Data Cloud) and Kinetica (Real-time/Vector/OLAP)
- Ability to design Property Graphs or RDF schemas that map enterprise entities into a machine-readable 'World Model.'
- Deep knowledge of data orchestration patterns (Change Data Capture, Streaming, and Batch) to ensure data freshness
- Strong DBA skills—partitioning strategies, indexing, vacuuming, and resource scaling in cloud-native environments
- Experience with tools like Cube or dbt Semantic Layer to provide a consistent 'Language' for AI agents to query
- Knowledge of RBAC and Row-Level Security (RLS) within an AI context—ensuring agents only 'see' what they are authorized to access
- Experience designing API-first data layers that agents can use as 'Tools' (e.g., function calling)