AI Engineer

Jasint•Annapolis Junction, MD

1d•Onsite

About The Position

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.

Requirements

5–10+ years of experience in AI/ML engineering, data engineering, or advanced analytics
Experience with: GCCS ecosystem (data sources, COP, system interfaces)
Experience with: JPES / JOPES processes and systems
Proficiency in: Python, and ML frameworks (TensorFlow, PyTorch, Scikit-learn)
Proficiency in: Data engineering tools (SQL/NoSQL, Spark, Kafka, ETL pipelines)
Experience deploying models in: Cloud environments (AWS GovCloud, Azure Government)
Experience deploying models in: Containerized environments (Docker, Kubernetes)
Understanding of: DoD cybersecurity requirements (RMF, STIGs, Zero Trust)
Understanding of: Data governance, labeling, and model validation in classified environments
Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or related field
Knowledge/Skills: AWS/Azure AI/ML Specialty
Knowledge/Skills: Security+ / CISSP (DoD 8570/8140 compliant)

Nice To Haves

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)
Experience with: Geospatial analytics (e.g., NGA data, GIS tools)
Experience with: Natural Language Processing (NLP) for planning documents and operational reporting
Experience with Palantir, DataBricks, or similar DoD data platforms

Responsibilities

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)