AI Data Governance Specialist

Overview

Job Title: AI Data Governance Specialist

Location: Columbus, OH

Duration: 06+ Months

We are seeking an AI Data Governance Specialist to support our AI engineering initiatives by ensuring compliance, security, and ethical use of data across AI systems. This role bridges data governance and AI development, enabling safe and effective deployment of AI solutions aligned with regulatory requirements and organizational standards.

• Collaborate with AI engineering teams to define and enforce data governance policies for AI models and pipelines.
• Implement data quality, lineage, and classification frameworks to support AI training and inference processes.
• Ensure compliance with regulatory standards (e.g., NIST AI RMF, ISO/IEC 42001, GDPR, CMMC, DFARS) and internal governance policies.
• Develop and maintain metadata strategies, including embedding and vector store management for Retrieval-Augmented Generation (RAG) architectures.
• Partner with security and compliance teams to manage risk assessments for AI data usage and model outputs.
• Support responsible AI practices, including bias detection, transparency, and explainability requirements.
• Provide guidance on data retention, lifecycle management, and secure handling of sensitive information (e.g., PII, CUI).

• Bachelor’s or Master’s degree in Data Science, Information Governance, Computer Science, or related field.
• Strong understanding of data governance principles, AI/ML workflows, and cloud-based environments (Microsoft Azure preferred).
• Experience with Microsoft Purview, Power Platform, and AI governance frameworks.
• Familiarity with AI model lifecycle, including training data preparation, embeddings, and RAG strategies.
• Knowledge of regulatory compliance (DFARS, CMMC, ITAR, FedRAMP) and ethical AI standards.
• Excellent communication skills to translate technical requirements into clear governance policies.

• Hands-on experience with Azure AI Foundry, Copilot Studio, or similar AI platforms.
• Understanding of data security controls, sensitivity labels, and DLP policies.
• Ability to work cross-functionally with engineering, compliance, and business stakeholders.