AI Data Engineer Sr (on-site)

Lockheed Martin•Fort Worth, CA

1d•Onsite

About The Position

We are seeking a Senior AI Data Engineer to support mission-critical, classified programs. This role involves designing and maintaining secure, scalable data infrastructure that enables advanced AI/ML capabilities in highly controlled environments. The ideal candidate has experience working within classified or regulated systems and understands the unique constraints of secure data engineering, including semantic data modeling and ontology-driven architectures.

Requirements

Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field
5+ years of experience in data engineering, including 2+ years supporting AI/ML systems
Strong proficiency in Python, NiFi, SQL
Experience with distributed data processing frameworks (e.g., Spark or similar)
Familiarity with secure cloud environments (e.g., AWS GovCloud, Azure Government) or on-prem systems
Must be a US Citizen for consideration due to security clearance requirements.

Nice To Haves

Active Secret clearance
Master’s degree in a related technical field
Preferred experience working in classified, regulated, or highly secure environments
Hands-on experience with semantic technologies, including RDF, OWL, and SPARQL
Understanding of data security principles, including encryption, access control, and auditing
Experience designing and building ontologies, taxonomies, or knowledge graphs
Experience with graph databases (e.g., Neptune, Stardog, Blazegraph)
Familiarity with real-time streaming technologies (e.g., Kafka) in classified settings
Experience with DoD/IC data platforms and compliance frameworks (e.g., RMF, NIST 800-53)
Exposure to AI/LLM pipelines integrated with semantic layers
Prior experience supporting defense, intelligence, or federal government programs

Responsibilities

Design, build, and maintain secure data pipelines for classified AI/ML workloads
Develop data architectures supporting both batch and real-time processing in air-gapped or restricted environments
Design and implement ontology-driven data models to support knowledge representation and reasoning
Develop and query semantic data stores using technologies such as RDF and SPARQL
Collaborate with data scientists, analysts, and mission stakeholders to operationalize AI models and knowledge graphs
Implement rigorous data validation, lineage, and governance controls in compliance with security requirements
Manage data ingestion, transformation, and storage across secure platforms, including graph and semantic databases
Optimize performance and reliability of large-scale data systems under constrained environments
Enforce data security, access controls, and auditing standards
Support deployment and monitoring of AI/ML models in secure production environments