AI and Metadata Engineer

Job Overview We are seeking an experienced AI and Metadata Engineer to design and implement AI-assisted capabilities for enterprise metadata, data extraction, lineage, and governance. The role will focus on transforming unstructured and structured information into reliable metadata and evidence models while applying normalization, confidence scoring, evaluation, and bounded lineage principles. Key Responsibilities • Design AI-assisted extraction solutions to identify and capture metadata from enterprise data sources. • Develop structured observations and evidence models to represent extracted metadata and supporting evidence. • Build normalization and standardization processes for metadata across diverse systems and data domains. • Define and implement confidence scoring and confidence rules for AI-generated observations. • Develop evaluation frameworks to measure extraction accuracy, completeness, consistency, and model performance. • Design bounded lineage services to establish traceable relationships between source data, extracted metadata, transformations, and downstream assets. • Collaborate with data architects, engineers, governance teams, and AI/ML teams to establish scalable metadata solutions. • Establish technical standards for AI-assisted extraction, validation, lineage, and metadata quality. • Support integration of AI/ML capabilities with enterprise data platforms and metadata repositories. • Ensure solutions are explainable, auditable, scalable, and appropriate for regulated financial-services environments. Required Skills • 7+ years of experience in Data Engineering, Metadata Engineering, Data Architecture, or related disciplines. • Strong experience with metadata management, data lineage, data extraction, and data governance. • Experience implementing AI/ML-assisted information extraction from structured and unstructured data. • Strong understanding of LLMs, NLP, prompt engineering, or AI-assisted extraction techniques. • Experience designing canonical/structured data models, evidence models, and normalization frameworks. • Knowledge of confidence scoring, validation rules, evaluation methodologies, and data-quality frameworks. • Experience building or integrating lineage services, metadata APIs, or data catalog solutions. • Strong programming experience with Python and familiarity with APIs, data processing, and cloud-based services. • Experience with enterprise data platforms, databases, and modern cloud technologies. • Excellent understanding of data governance, traceability, auditability, and regulatory requirements in financial services. Preferred • Experience with Generative AI, LLMs, RAG, or agentic AI applied to enterprise data. • Experience with metadata/catalog platforms such as Collibra, Alation, Informatica, Microsoft Purview, or similar technologies. • Experience with graph databases or graph-based lineage models. • Experience working in banking or other highly regulated environments. • Familiarity with model evaluation, observability, and responsible AI practices.