AI Engineer

Booz Allen Hamilton•Usa, MD

12d

About The Position

As an AI Model SME, you will design, test, optimize, and operationalize AI and machine learning models across cloud, edge, and hybrid environments. You will help set technical direction for mission-critical AI solutions by selecting appropriate architectures, building deployment pipelines, and integrating models with enterprise and mission systems. You will work with data engineers, data scientists, cloud and network architects, and ISSE partners to ensure models are supported by secure, scalable infrastructure and high-quality data pipelines. You will evaluate emerging AI and ML frameworks, guide feature engineering, support fine-tuning and retraining, and implement monitoring to identify performance drift and other operational issues. The role supports mission partners in keeping deployed models performant, reliable, and aligned with operational objectives.

Requirements

Experience with programming languages such as Python or Rust.
Experience developing, training, validating, and deploying AI and ML models.
Experience optimizing AI and ML models.
Knowledge of computing, storage, and networking requirements for model training, tuning, and inference.
Knowledge of model evaluation techniques.
Ability to design and implement model deployment pipelines and MLOps workflows.
Ability to implement monitoring frameworks for model drift, performance degradation, and operational issues.
Active TS/SCI clearance with a polygraph is required.
High school diploma or GED and 6+ years of experience with data science or AI and ML engineering, or a bachelor's degree and 4+ years of experience with data science or AI and ML engineering.

Nice To Haves

Experience with distributed compute frameworks.
Experience working in mission-focused or national security environments.
Experience evaluating new AI model architectures.
Knowledge of secure AI engineering practices, such as adversarial robustness, model governance, or NIST AI RMF.
Bachelor's degree.

Responsibilities

Design, test, optimize, and operationalize AI and ML models across cloud, edge, and hybrid environments.
Select suitable model architectures and provide technical direction for mission-critical AI solutions.
Implement model deployment pipelines and integrate models with enterprise and mission systems.
Collaborate with data engineers, data scientists, cloud and network architects, and ISSE partners on secure infrastructure and high-quality data pipelines.
Evaluate emerging AI and ML frameworks and guide feature engineering approaches.
Support model fine-tuning and retraining cycles.
Implement monitoring frameworks to identify model drift, performance degradation, and operational issues.
Help mission partners understand AI and ML technologies and keep deployed models aligned with operational objectives.