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AI & Data Science Engineer
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Based on Maryland data
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What they do
A Generative Artificial Intelligence Engineer develops, designs, and manages generative models and algorithms that support the generation of new content in the form of images, text, audio, and other multimedia. They utilize GPTs, GANs, VAEs, and other deep learning architectures to craft systems capable of generating data. May work with data scientists, machine learning engineers, and software developers.
$119,525 / year median in Maryland
Job Description
AI & Data Science Engineer
ResponsibilitiesDevelop 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.
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.