Data Engineer; AI Subject Matter Expert; SME TS​/SCI Belvoir, VA - Nolan Bldg

Position: Data Engineer (AI) Subject Matter Expert (SME) (4799) (TS/SCI) (Ft. Belvoir, VA - Nolan Bldg)

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SMX is seeking a Data Engineer (AI) Subject Matter Expert (SME) to spearhead the development and sustainment of data pipelines and data services that enable AI/ML capabilities within Army Intelligence mission environments. This role defines standards, develops and implements end‑to‑end data pipeline strategy, and guides a small team to deliver reliable, secure, and observable data services for training, inference, and analytics.

The Data Engineer (AI) SME partners with AI/ML engineers, analysts, platform teams, and mission leadership to align data capabilities with operational outcomes, security, and governance.

This is a full‑time onsite position in Ft. Belvoir, VA.

Essential Duties & Responsibilities Planning & Stakeholder Alignment

• Translate mission needs into a data engineering roadmap, delivery plans, and measurable outcomes for AI/ML use cases.
• Serve as primary technical point of contact for data dependencies across model development, analytics, and platform teams; drive cross‑team decision making and risk trade‑offs.
• Review and recommend designs, requests, and deployments from team members; develop quality standards and coding conventions.

Data Architecture & Platform Enablement

• Define reference architectures and patterns for ingestion, ELT/ETL, lake/lakehouse/warehouse integration, and feature data delivery.
• Select and standardize pipeline tooling and storage/layout strategies to balance performance, cost, and security.
• Establish schema, partitioning, and lifecycle strategies to support model retraining, reproducibility, and rollback.

Data Pipeline Development & Maintenance

• Design and oversee ETL/ELT pipelines that supply structured and unstructured data to AI/ML workflows.
• Establish and ensure compliance with SLOs/SKIs for data freshness, latency, and completeness; oversee and implement autoscaling and performance tuning across cloud/hybrid environments.
• Implement and oversee data ingestion, cleansing, transformation, normalization, and feature preparation steps according to established methods.
• Ensure pipelines are reliable, repeatable, and well‑documented.

Data Quality, Validation & Monitoring

• Perform data profiling, validation, and integrity checks to ensure high‑quality inputs to AI/ML models.
• Monitor data pipeline performance and data flow health; document and elevate issues to senior engineers.
• Drive issue triage and root‑cause analysis; lead post‑incident reviews and preventative improvements.
• Contribute to improving data observability and traceability.

Deployment & Monitoring

• Lead employment of Agile methodologies for project management.
• Manage deployment pipelines, containerization, and CI/CD workflows for AI services in the cloud to ensure reproducible data operations.
• Implement and oversee robust monitoring, observability, and performance tracking for AI‑supporting data systems.

Training & Support

• Provide training and technical support to military personnel to ensure effective adoption and utilization of AI technologies.
• Ensure comprehensive documentation of integration architecture, processes, and operational dependencies, to include data structures, transformation logic, data lineage, pipeline workflows, and operational procedures.
• Mentor and coach engineers; build repeatable playbooks and raise the team’s technical maturity.

Compliance & Security

• Ensure compliance with military security, privacy and governance standards for AI‑supporting data systems.
• Ensure processes and procedures leverage changes in data engineering and AI/ML governance best practices.

Required Skills, Experience & Education Security

• Active TS security clearance and eligible for SCI and NATO read‑on prior to starting work
• Meet all requirements to receive a privileged user account on a TS/SCI information system (e.g., Army Cloud Computing Service Provider) prior to starting work. The requirements are currently defined in DoDD 8140.01.
• Security+ or related DoDD 8140‑relevant certification.

Education and Experience

• Master’s degree in Computer Science, Data Science, Engineering, or a related technical field.
• 7+…