Manager, Data Architecture & AI Enablement

Job description

What happens when your architecture becomes the backbone of enterprise strategy? If you have five or more years of hands-on data architecture and engineering experience on Databricks and Azure — plus real delivery with AI patterns like retrieval-augmented generation and document intelligence - we want to speak with you! We are seeking a Manager, Data Architecture & AI Enablement, to join our AI & Data Center of Excellence in Richmond, VA. with a hybrid work schedule.

Relocation benefits will be provided. In this role, you will own the target-state data architecture for Laboratory Services, Regulatory Affairs, R&D, and Product Innovation, while delivering governed, production-ready AI capabilities for scientists and regulatory professionals. As part of the AI & Data Center of Excellence, you will define and execute the architecture for functions historically outside the enterprise data strategy, ensuring scalable, compliant data and AI solutions in a highly regulated environment.

Combining data architecture and AI enablement, you will drive integration, data modeling, semantic layer, and data-readiness decisions; establish retrieval, document intelligence, and conversational AI patterns; and ensure data is not only delivered but also adopted through AI capabilities actively used in production.

What you’ll be doing

Own the target-state data architecture for these domains — source integration, layered models, and the curated semantic layer that serves analytics and AI. Lead source discovery and integration across LIMS, SDMS, electronic lab notebooks, regulatory information management, quality management and product lifecycle systems, plus SharePoint and file-based sources. Design the data models and semantics for studies, samples, methods, results, specifications, formulations and submissions, using conformed dimensions, controlled vocabularies and consistent units of measure.

Deliver AI enablement

document intelligence over scientific and regulatory content, retrieval-augmented generation, governed conversational access, and the evaluation and monitoring that keep it trustworthy. Build and oversee production pipelines on Databricks and Azure — medallion layering with Delta, change data capture, schema evolution, observability and cost management. Govern these domains in Unity Catalog and Microsoft Purview, aligned to Microsoft Entra ID groups and Azure role assignments, so access, lineage and cataloging are enforced once.

Design for a regulated environment

validation, audit trails, versioned transformations, data quality rules as code, and responsible AI standards for every model and agent released. Lead and coach a small team of architects and engineers, and set the design, code and acceptance standards that onshore and offshore delivery partners build to. Work forward deployed with laboratory, regulatory and product teams, shipping working data products against real feedback rather than requirements documents.

We want you to have: Bachelor's degree in Computer Science, Information Systems, Engineering, a physical or life science, or a related technical field. 5+ years of hands-on data architecture and data engineering experience, with a portfolio of pipelines and data models you personally designed and built.

Hands-on integration experience with laboratory and regulatory systems

LIMS, SDMS, electronic lab notebooks, regulatory information management platforms, quality management systems such as TrackWise, and product lifecycle or product data management tools. Strong command of the Databricks/Microsoft data and AI stack: Azure Data Factory, Azure Data Lake Storage Gen2, Microsoft Entra ID and Azure RBAC, Microsoft Purview, and Azure AI or Microsoft Fabric services.

Practical delivery experience with modern AI patterns

retrieval-augmented generation, embeddings and vector retrieval, document intelligence over unstructured content, agentic and conversational access to curated data, and the data readiness and evaluation work underneath them.