AI & Data Science Engineer with Security Clearance

Responsibilities
Develop mission-driven AI/ML models, analytics workflows, automation solutions, and agentic AI systems supporting CECOM and Army requirements. Collaborate daily with government engineers and analysts to provide technical guidance, training moments, and knowledge transfer. Build and maintain mission data pipelines, dashboards, Power BI solutions, retrieval pipelines (RAG), and agentic workflows. Design and implement Generative AI, Agentic AI, and multi-agent solutions using frameworks such as LangChain, Semantic Kernel, AutoGen, Strands, CrewAI, and LangGraph.

Integrate LLMs securely with mission data, memory systems, vector search, and agent orchestration aligned with compliance and cyber requirements. Support cloud-native AI practices including MLOps/AIOps, CI/CD pipelines, monitoring, and responsible AI governance. Produce documentation, sustainment plans, and handoff materials to ensure long-term government ownership. Coordinate with teams, mission partners, and stakeholders to align solutions with operational needs and modernization objectives.

Experience Requirements
4+ years delivering AI/ML solutions, including at least 1 year with Generative AI, Agentic AI, or multi-agent systems.
2+ years hands-on development using Python.
1+ year building agentic systems using LangChain, Semantic Kernel, AutoGen, Strands, CrewAI, LangGraph, or similar frameworks. Experience with Azure, AWS, or GCP for AI/ML workloads. Experience building ML workflows, data pipelines, automation processes, or analytics systems. Ability to translate functional or mission needs into technical solutions. Active Secret Clearance, TS preferred.

Preferred: DoD, Army, or federal mission support; capability development and training in government settings; multi-agent systems for automation and decision support; LLM prompt engineering, fine-tuning, secure RAG; MLOps/AIOps and CI/CD; APIs, microservices, event-driven architectures; Microsoft Power Apps.
Preferred Azure tools: Azure Machine Learning, Synapse, Databricks, Cognitive Services, Cognitive Search with Vector Search, Microsoft Fabric.
Preferred data and analytics tools: Python, R, Power BI, Power Automate, SharePoint.
Preferred certifications: Azure, AWS, GCP, ML/AI engineering, or solutions architecture.