About the role

Associate Architect Data Engineer spearheading development of innovative data layers for Agentic AI. Collaborating on hybrid-database environments across Snowflake and Kinetica, driving client technical strategy.

Responsibilities

Spearhead the structural development of an innovative data layer tailored for Agentic AI.
Orchestrate hybrid-database environments across Snowflake and Kinetica while acting as the cornerstone for client technical strategy and governance.
Design the end-to-end blueprint for a modern enterprise data architecture encompassing all layers such as Ingestion Management, Lakehouse storage, Transformation & Orchestration, Semantic & Context, Serving & Consumption, Governance, and seamlessly integrating structured, unstructured, and graph data for consumption by 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 data clusters (BigQuery/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.

7+ years of experience in Data Engineering/Architecture.
Proven expertise in architecting for cloud lakehouses (BigQuery / Cosmos / Snowflake / Kinetica) and building Vector DBs (Milvus / Qdrant / Cosmos / Azure AI Search).
Ability to design Property Graphs or RDF schemas that map enterprise entities to serve complex clinical traversal queries.
Deep knowledge of data orchestration patterns (Change Data Capture, Streaming, and Batch) to ensure data freshness.
Strong DBA skills—partitioning strategies, indexing, sharding, vacuuming, and resource scaling in cloud-native environments.
Hands-on experience with vector stores, knowledge graphs, and semantic layer design to enable intelligent agent workflows.
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).

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 !