IT Program Manager - Data Integration and AI Governance

About the role

The Command Information Office of Naval Facilities Engineering Systems Command is seeking an IT Program Manager to act as program lead for a significant program with command-wide or enterprise-wide impact. The role covers program management, data integration, and the governance of AI and machine learning across the enterprise data ecosystem.

Key responsibilities

• Analyze and evaluate quantitative and qualitative data to support strategic decision making.
• Lead IT and data project teams, managing hardware, software, data pipelines, APIs, systems, services, engineering, integration and documentation.
• Explore, adopt and govern AI and machine learning capabilities, establishing AI governance protocols that comply with GenAI.mil guidelines, DOW directives and unbiased AI principles.
• Serve as the Command's technical authority on data integration, interoperability and enterprise data flow.
• Design, implement and manage data integration strategies that connect legacy operational technology systems with modern cloud-based data lakehouse architectures.
• Assess and improve management processes, IT systems and data flow architectures using qualitative and quantitative methods.

Required profile

• At least one year of specialized experience at or equivalent to GS-13 grade level in the Federal service, or equivalent experience in the private or public sector.
• Experience building consensus among technical vendors, database administrators, data stewards and other stakeholders, and resolving integration bottlenecks.
• Ability to apply project management principles (cost, schedule, resources, POA&M, AOA) to IT and data acquisitions.
• Experience supporting the development and implementation of AI and machine learning capabilities, including generative AI and large language model applications.

Required skills

• Enterprise data management and architecture, including data lakehouse platforms, API-based data exchange and cloud data services.
• Data governance: data standards, metadata management, data stewardship, schema governance and data quality controls.
• Master data management, including data domains, reference data, data lineage and data reconciliation.
• Data engineering: scalable data pipelines, data models and curated data sets.
• Knowledge of dashboard visualization tools.