AI Engineer
Role details
Job location
Tech stack
Job description
- Design, develop, and deploy AI/ML models to support GCCS and JPES mission workflows (e.g., force planning, course of action analysis, logistics forecasting)
- Integrate AI capabilities into C2 systems and data pipelines, enabling real-time analytics and decision support
- Engineer and maintain data pipelines for structured and unstructured data across GCCS, JPES, and related systems
- Implement data fusion and knowledge graph solutions to unify operational, intelligence, and logistics data
- Develop AI-enabled capabilities for predictive analytics, anomaly detection, and decision automation
- Deploy models in cloud and edge (DDIL) environments, ensuring resilience and low-latency performance
- Apply MLOps best practices (CI/CD, model versioning, monitoring) within DoD DevSecOps ecosystems (e.g., Platform One)
- Ensure compliance with DoD AI governance, ethical AI principles, RMF, and Zero Trust Architecture
- Support Cross Domain Solution (CDS) integration for secure AI data flows across classification levels
- Collaborate with operators and planners to align AI outputs with JOPP / JPES workflows
- Produce technical documentation, model explainability artifacts, and architecture inputs (DoDAF views)
Requirements
Clearance Requirements: This position requires a current and active Secret clearance (TS/SCI preferred), We are seeking an innovative AI Engineer with experience in Global Command and Control System (GCCS) and Joint Planning and Execution Services (JPES) to develop and integrate AI/ML capabilities into Joint Command and Control (C2) environments. This role focuses on enabling data-driven decision advantage by embedding AI/ML into operational planning, execution workflows, and real-time situational awareness systems across DoD networks, * 5 10+ years of experience in AI/ML engineering, data engineering, or advanced analytics
- Experience with:
- GCCS ecosystem (data sources, COP, system interfaces)
- JPES / JOPES processes and systems
- Proficiency in:
- Python, and ML frameworks (TensorFlow, PyTorch, Scikit-learn)
- Data engineering tools (SQL/NoSQL, Spark, Kafka, ETL pipelines)
- Experience deploying models in:
- Cloud environments (AWS GovCloud, Azure Government)
- Containerized environments (Docker, Kubernetes)
- Understanding of:
- DoD cybersecurity requirements (RMF, STIGs, Zero Trust)
- Data governance, labeling, and model validation in classified environments
Education:
- Bachelor s or Master s degree in Computer Science, Data Science, Artificial Intelligence, or related field
Knowledge/Skills:
- AWS/Azure AI/ML Specialty
- Security+ / CISSP (DoD 8570/8140 compliant)
Preferred Qualifications:
- Experience supporting DISA, Joint Staff, or Combatant Command C2 systems
- Familiarity with JADC2, CJADC2, and data-centric warfare concepts
- Experience with:
- Knowledge graphs / ontologies (e.g., RDF, OWL)
- Geospatial analytics (e.g., NGA data, GIS tools)
- Natural Language Processing (NLP) for planning documents and operational reporting
- Experience with Palantir, DataBricks, or similar DoD data platforms
Physical Demands
This is largely a sedentary role; however, some filing is required. The ability to move files, open filing cabinets, and bend or stand as necessary would be required.