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# AI Engineer (TS/SCI with Polygraph)

- **Company:** Red Alpha
- **Location:** Anne Arundel County, MD, United States
- **Experience:** Expert
- **Salary:** $170,000.0 - $230,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Cloud Computing, Machine Learning, Software Architecture, Cloud Platform System, Information Technology, Production Code, Data Analytics, Machine Learning Operations
- **Published:** November 4, 2026
- **Apply:** https://www.thejobnetwork.com/job/c9c94e3e-9d3d-413a-b823-c68ab6a3d377/ai-engineer-tssci-with-polygraph

## About the Role

* 10 + years of relevant experience with AI, Data Science and Development

## Description

We're looking for an AI Engineer to work closely with system and software engineers to design, prototype, and integrate AI advancements into the existing RAD architecture. This is a transformative position focused on building solutions that augment human intelligence, streamline workflows, and enhance the overall effectiveness of intelligence operations., * A Bachelor of Science degree in Computer Science or a related field from an accredited institution. Four (4) addn'l years of relevant experience may be considered in lieu of a degree

 * Design and Development: Lead the design and development of AI-driven solutions from conception to deployment, ensuring seamless integration with the existing software architecture. This includes prototyping new models, writing production-quality code, and maintaining existing AI systems.
 * Collaboration and Communication: Serve as a key technical liaison, collaborating with cross-functional teams including system engineers, software developers, and domain experts. Effectively present and articulate recommended AI approaches, discussing the tradeoffs and implications of different implementations with both technical and non-technical stakeholders.
 * Data Analysis and Modeling: Conduct Exploratory Data Analysis (EDA) on diverse datasets (both structured and unstructured) to inform the data model, identify data quality issues, and determine optimal input formats for AI models.
 * Model Building and Evaluation: Develop, train, and evaluate a variety of machine learning models, ensuring they meet performance and reliability requirements. Implement robust testing and validation strategies to ensure models are accurate and unbiased.
 * Continuous Improvement: Stay current with the latest advancements in AI and machine learning, continuously seeking opportunities to apply new technologies and methodologies to improve existing systems and solve complex problems.
 * Cloud Platforms: Have experience with the Amazon Web Services (AWS) cloud computing platform and machine learning operations (MLOps) tools for deploying and managing machine learning models at scale.