AI Engineer

Booz Allen Hamilton•Fort Meade, MD

26d•$99,000 - $225,000

About The Position

As an AI Model SME, you will design, test, optimize, and operationalize AI and ML models across cloud, edge, and hybrid environments. You will help set technical direction for mission-critical AI solutions by selecting suitable architectures, implementing deployment pipelines, and integrating models with enterprise and mission systems. You will collaborate with data engineers, data scientists, cloud and network architects, and ISSE partners to support secure, scalable infrastructure and high-quality data pipelines. The role also involves evaluating emerging AI and ML frameworks, guiding feature engineering, supporting fine-tuning and retraining, and implementing monitoring to detect performance drift and other issues. You will help mission partners navigate AI and ML technologies and keep deployed models performant, reliable, and aligned with operational objectives. Applicants selected will be subject to a security investigation and must meet eligibility requirements for access to classified information. TS/SCI clearance with a polygraph is required. The position’s projected annualized compensation range is $99,000 to $225,000. Booz Allen describes benefits including health, life, disability, financial and retirement benefits, paid leave, professional development, tuition assistance, work-life programs, dependent care, and recognition awards. The work model is not specified for this position; the posting explains that remote, hybrid, or onsite arrangements may have additional expectations if applicable.

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.
HS 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 best 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 model architectures and set technical direction for mission-critical AI solutions.
Implement model deployment pipelines and integrate models with enterprise and mission systems.
Collaborate with data engineering, data science, cloud and network architecture, and ISSE partners on secure infrastructure and data pipelines.
Evaluate emerging AI and ML frameworks and guide feature engineering approaches.
Support model fine-tuning and retraining cycles.
Implement monitoring frameworks to detect model drift, performance degradation, and operational issues.
Help mission partners assess AI and ML technologies and keep deployed models aligned with operational objectives.