Role:Architect Data Engineer - AI Platforms
Experience Level:10+ yrs
Work Location:US East/Canada (Remote)
Role Overview:Lead the architectural vision for a next-generation data layer designed specifically for Agentic AI. You will define high-performance schemas, orchestrate complex hybrid-database environments (Snowflake/Kinetica/NoSQL), and serve as the primary technical liaison for our customers. This is a high-visibility role blending deep technical governance with strategic relationship development.
Key Responsibilities:- System Architecture: Design the end-to-end blueprint for a modern data layer that seamlessly integrates structured, unstructured, and relational (Graph) data for AI agents.
- Schema & Ontology Design: Define multi-tenant schemas and Knowledge Graph ontologies that allow LLM agents to perform complex reasoning and cross-domain data retrieval.
- Database Administration & Governance: Oversee the health, security, and performance optimization of our data clusters (Snowflake/Kinetica), ensuring 99.9% availability for mission-critical AI workflows.
- Strategic Client Fronting: Act as the "Face of Engineering" for the customer. Lead discovery workshops, manage technical expectations, and align the architectural roadmap with their business objectives.
- Performance Engineering: Define performance and observability standards to ensure low-latency, accurate, reliable data retrieval for real-time agentic AI workloads.
Basic Qualifications:- System Architecture: Design the end-to-end blueprint for a modern data layer that seamlessly integrates structured, unstructured, and relational (Graph) data for AI agents.
- Schema & Ontology Design: Define multi-tenant schemas and Knowledge Graph ontologies that allow LLM agents to perform complex reasoning and cross-domain data retrieval.
- Database Administration & Governance: Oversee the health, security, and performance optimization of our data clusters (Snowflake/Kinetica), ensuring 99.9% availability for mission-critical AI workflows.
- Strategic Client Fronting: Act as the "Face of Engineering" for the customer. Lead discovery workshops, manage technical expectations, and align the architectural roadmap with their business objectives.
- Performance Engineering: Establish benchmarks for data latency and retrieval accuracy, ensuring the data layer can keep pace with the real-time demands of agentic execution.
- The Hybrid Stack: Proven expertise in architecting for Snowflake (Data Cloud) and Kinetica (Real-time/Vector/OLAP).
- Knowledge Graph Mastery: Ability to design Property Graphs or RDF schemas that map enterprise entities into a machine-readable "World Model."
- Advanced ETL/ELT Strategy: Deep knowledge of data orchestration patterns (Change Data Capture, Streaming, and Batch) to ensure data freshness.
- Database Internals: Strong DBA skills-partitioning strategies, indexing, vacuuming, and resource scaling in cloud-native environments.
Good to Have (The "Agentic" Edge):- Semantic Layer Design: Experience with tools like Cube or dbt Semantic Layer to provide a consistent "Language" for AI agents to query.
- Security & Privacy: Knowledge of RBAC and Row-Level Security (RLS) within an AI context-ensuring agents only "see" what they are authorized to access.
- Tooling for Agents: Experience designing API-first data layers that agents can use as "Tools" (e.g., function calling).
What's in it for YOU at Quantiphi:- Make an impact at one of the world's fastest-growing AI-first digital engineering companies.
- Upskill and discover your potential as you solve complex challenges in cutting-edge areas of technology alongside passionate, talented colleagues.
- Work where innovation happens - work with disruptive innovators in a research-focused organization with 60+ patents filed across various disciplines.
- Stay ahead of the curve-immerse yourself in breakthrough AI, ML, data, and cloud technologies and gain exposure working with Fortune 500 companies.
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
