AI Data engineer

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Description

Key Responsibilities AI Data Architecture & Platform Support Architect and optimize high-throughput data pipelines and unstructured data processing frameworks to directly power the enterprise AI Foundation Platform. Co-own the vector infrastructure alongside the AI Engineer Specialist, ensuring optimized embedding storage, indexing strategies, and fast vector search retrieval. Build automated ETL/ELT pipelines capable of transforming raw enterprise data into AI-ready formats (chunking, metadata tagging, and cleaning). Data Governance, Metadata & Cataloging Implement metadata pipelines for comprehensive data catalog and data dictionary services, including schema capture, lineage tracking, and audit logging. Enforce data governance, access controls, and privacy compliance across all data stores used for training, fine-tuning, and RAG retrieval. Design and maintain operational data lineage to ensure transparency and auditability of data flowing into production AI models. Advanced AI Component Integration Develop and tune robust data ingestion pipelines for OCR, NLP processing, recommendation systems, and multi-modal AI inputs. Optimize data tiering and caching strategies to reduce latency and infrastructure costs for live enterprise AI workloads. Build secure, scalable data connectors linking legacy enterprise databases with modern LLM frameworks and autonomous agents. Collaboration & Data Excellence Partner directly with the AI Engineer Specialist to ensure seamless data deliv

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