AI Engineer

About This Role

As an AI Engineer at NSA, you will design and implement mission-critical AI systems to advance intelligence collection, processing, and reporting. This role involves building, deploying, and maintaining artificial intelligence (AI) systems at scale.

Responsibilities

• Lead or contribute to cross-functional teams to develop and operationalize AI solutions
• Apply modern engineering techniques to design, develop, deploy, and maintain end-to-end AI workflows
• Adapt and integrate diverse AI model architectures to address complex mission-critical challenges
• Monitor and maintain AI products through systematic identification of performance degradation and computational inefficiency
• Maintain knowledge of current AI research and adapt emerging techniques to intelligence applications
• Test and evaluate AI solutions against mission requirements and produce actionable recommendations

Requirements

• Ability to pass the Data Science Examination (DSE) covering statistics, mathematics, and computer science
• Associate's degree plus 2 years relevant experience OR Bachelor's degree with no experience (Computer Science/Engineering)
• Associate's degree plus 3 years relevant experience OR Bachelor's degree with 1 year relevant experience (other specified fields)
• Relevant experience in AI/ML solutions, distributed systems, platform/cloud engineering, deep learning, DevOps, MLOps, software engineering, automated testing, or containerization

Qualifications

• Associate's, Bachelor's, Master's, or Doctoral degree in Computer Science, Engineering, Information Systems, Information Technology, Mathematics, Applied Mathematics, Statistics, Applied Statistics, Operations Research, Artificial Intelligence, Data Science, or Physical or Biological Sciences with specific coursework for non-ABET accredited engineering degrees.
• Relevant experience in implementing production scale AI/ML solutions, distributed model training, distributed AI/ML systems, AI/ML performance monitoring, platform engineering, cloud engineering, developing deep learning models, neural networks, sustaining/maintaining AI/ML models, implementing AI/ML algorithms, AI/ML model development and deployment, DevOps, MLOps, cloud infrastructure management, software engineering, automated testing, or containerization.

Skills

* Required skills

Benefits