AI Engineer

Booz Allen Hamilton•Fort Meade, MD

25d•$99,000 - $225,000

About The Position

The AI Engineer will develop, optimize, deploy, and continuously improve AI and machine learning models that support mission needs. The role includes designing, testing, optimizing, and operationalizing models across cloud, edge, and hybrid environments; selecting suitable architectures; building deployment pipelines; and integrating models with enterprise and mission systems. The engineer will collaborate with data engineers, data scientists, cloud and network architects, and ISSE partners to support models with secure, scalable infrastructure and high-quality data pipelines. The position also provides technical leadership by evaluating AI and ML frameworks, guiding feature engineering, supporting fine-tuning and retraining, and implementing monitoring to identify model drift and performance issues. The engineer will help mission partners navigate evolving AI and ML technologies and keep deployed models reliable, performant, 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 across model training, tuning, and inference phases.
Knowledge of model evaluation techniques.
Ability to design and implement model deployment pipelines and MLOps workflows.
Ability to implement monitoring frameworks for detecting model drift, performance degradation, and operational issues.
TS/SCI clearance with a polygraph.
High school diploma or GED and at least 6 years of experience with data science or AI and ML engineering, or a bachelor's degree and at least 4 years of such experience.

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 best practices such as adversarial robustness, model governance, or NIST AI RMF.
Bachelor's degree.

Responsibilities

Develop, train, validate, deploy, and optimize AI and ML models.
Design, test, and operationalize models across cloud, edge, and hybrid environments.
Select appropriate model architectures and integrate models with enterprise and mission systems.
Design and implement model deployment pipelines and MLOps workflows.
Collaborate with data engineers, data scientists, cloud and network architects, and ISSE partners.
Evaluate AI and ML frameworks and emerging model architectures.
Guide feature engineering approaches and support fine-tuning and retraining cycles.
Implement monitoring frameworks to detect model drift, performance degradation, and operational issues.
Advise mission partners on AI and ML technologies and model lifecycle strategy.