Enterprise Data & AI Engineering Lead

Virginia Information Technologies Agency•Richmond, VA

3d•Hybrid

About The Position

The Department of Behavioral Health and Developmental Services (DBHDS) is seeking a highly skilled and experienced IT and Data professional to serve as the Enterprise Data & AI Engineering Lead. This position is critical to the successful implementation, maintenance, and scaling of DBHDS’s modern cloud-based data ecosystem. The Enterprise Data & AI Engineering Lead will provide hands-on support for the agency’s data management & AI efforts. In this capacity, the position will partner closely with business units to design and deliver cloud-based data & AI products, processes, and procedures that directly support their mission. The role will champion data-driven decision-making across the agency, provide process guidance to business units to help meet enterprise goals, and implement strategies, best practices, and standards aligned with the agency’s technology roadmap. The ideal candidate is a forward-thinking specialist who can seamlessly integrate modern, technology-enabled data practices while communicating effectively with stakeholders at all levels. The Enterprise Data & AI Engineering Lead will ensure the ongoing development, optimization, and reliability of the agency’s data platform and data products, supporting DBHDS’s mission to serve the community effectively.

Requirements

Experience managing and leading a Data or Data & AI Engineering initiative.
Experience in cloud-based data and AI ecosystems, including data engineering, data storage/administration, data consumption, governance.
Proficiency in data and analytics practices, including data mapping, transformation, modeling, integration, and ML/AI‑driven automation.
Experience with ETL/ELT tools (preferably AWS).
Experience building data and AI products in modern cloud ecosystems (AWS preferred), including agentic workflows and automated AI assistants.
IT skills across on‑premises and cloud technologies (AWS preferred).
Data engineering expertise using AWS native services and/or Snowflake.
Experience in database management and data solution design across SQL Server, AWS native services, and Snowflake.
Proficiency in scripting (preferably Python), including development of AI workflows, RAG pipelines, or agent‑based automations.
Experience with major cloud platforms such as AWS or Azure (AWS strongly preferred).
Understanding of Data Architecture, Data governance, DataOps practices.
Strong communication, interpersonal, and training skills.
Ability to collaborate across diverse technical and business teams.
Understanding of enterprise architecture (EA), IT governance, privacy, and compliance frameworks relevant to data and AI.
Experience designing and implementing highly scalable, fault‑tolerant data or AI systems.
Problem‑solving skills with a track record of addressing complex IT challenges.

Nice To Haves

Experience in IT and business/industry field.
Experience in cloud data engineering or related roles.
Relevant certifications (e.g., AWS Certified Solutions Architect, Microsoft Certified: Azure Solutions Architect, Snowflake , CDMP)

Responsibilities

Providing expertise in data and AI management for a modern cloud data ecosystem, mentoring staff and aligning skills across all data and AI disciplines, including data engineering, ML/AI engineering, and agentic automation workflows.
Creating value through data and AI exploitation by envisioning data-enabled and AI‑enabled strategies, and enabling business outcomes through a governed, cloud‑based data and AI ecosystem.
Championing modern data and AI management practices across the agency by providing technical leadership on cloud-ready ecosystems (e.g., AWS), modern data stores (e.g., Snowflake, DynamoDB), scripting tools (e.g., Python), and consumption layers (e.g., AWS native tools, Power BI, SnowSQL) including usage of approved models for use.
Leading Data and/or AI engineering efforts to design, develop, and operationalize AI capabilities, including single‑agent and multi‑agent workflows, retrieval‑augmented generation (RAG), and agent‑based automations aligned with enterprise security and compliance.
Organizing and leading working groups for data and AI governance to ensure oversight of policies, compliance, model accountability, data quality, and responsible AI practices.
Designing and leading the implementation of scalable data engineering and AI solutions to support enterprise feature development and capability creation on a modern cloud data and AI ecosystem.
Promoting data and AI literacy across business units, enabling broader adoption of cloud technologies and AI‑driven workflows for mission‑critical operations.
Providing technical leadership and expertise for project initiatives both on‑premises and in the cloud while championing modern data integration, AI engineering, development practices, and Data/ML Ops.
Driving innovation through prototypes and proofs of concept for emerging technologies, including AI agents, automated workflows, and advanced analytics to address business needs.
Reviewing and consolidating business plans, budgets, and forecasts related to enterprise data and AI management.
Collaborating with architects to design system components for data and AI platforms, define current and future states, and guide architectural decisions supporting the agency’s technology roadmap.
Serving as a subject matter expert for data architecture, AI architecture, design, context, and value across the organization, while supporting data quality, model lifecycle management, and process improvement.
Supporting contract management for vendors and resources supporting enterprise data and AI applications, analyzing requirements, and providing insights to technology stakeholders.
Driving transformation across all DBHDS business units by implementing best practices in data delivery, AI automation, and scalable cloud engineering.