Job Description
📋 Description Own architectural direction for AI across data platform to accelerate ingestion, modeling Architect an AI-assisted data pipeline factory with patterns, guardrails, and standards for Design and evolve AI-native tools and services on reusable architectural foundations. Define architecture for advanced ML/deep learning workloads, including vector and unified search Establish reference architectures, contracts, and standards for interoperable ML/AI data flows. Prevent fragmentation across AI/ML efforts by aligning end-to-end data organization patterns. 🎯 Requirements 7+ years of experience in data architecture, data platforms, and Big Data with ML engineering Deep technical and analytical background across Data Warehousing, Streaming, Big Data, and AI/ML Strong hands-on proficiency with Databricks as a data lakehouse, plus dbt/Spark and modern data Experience architecting ML/AI workloads including vector/semantic/unified search as durable Practical experience using AI tooling and agents to accelerate development with engineering Systems-first mindset toward AI, treating LLMs/agents as components within defined architectural
