Booz Allen Hamilton · 1 week ago
AWS Data & AI Engineer, Senior
Washington, DC
Full-time
Hybrid
Mid, Senior Level
$78K/yr - $176K/yr
4+ years expBooz Allen Hamilton is a company focused on building intelligent, scalable systems for the Federal Government. As an AWS Data and AI Engineer, you will design, build, and operationalize machine learning solutions on AWS, particularly leveraging Amazon SageMaker, to support secure and scalable ML pipelines.
ConsultingCyber SecurityIT InfrastructureManagement ConsultingSecurity
No H1B
U.S. Citizen Only
Responsibilities
Enable intelligent, scalable systems by engineering data pipelines and machine learning foundations that move models from experimentation to mission-ready deployment
Focus on designing, building, and operationalizing machine learning solutions on AWS, with a strong emphasis on Amazon SageMaker
Work alongside solution architects, data scientists, and application teams to deliver secure, scalable ML pipelines—supporting everything from data ingestion and feature engineering to model training, deployment, and monitoring in compliance-driven federal environments
Qualification
Required
4+ years of experience as a data engineer, ML engineer, or software engineer working with data-driven or ML-enabled systems
Experience designing and operating end-to-end ML workflows using Amazon SageMaker, including SageMaker Studio or Notebooks, training jobs and hyperparameter tuning, managed model endpoints and batch inference, SageMaker Pipelines, Model Registry, and experiment tracking
Experience building data pipelines and feature engineering workflows using AWS services, such as S3, Glue, Redshift, EMR, Athena, or Lambda
Experience with Python development for data processing and ML workloads and SQL
Experience deploying and managing containerized ML workloads using Docker, ECR, and AWS-managed compute
Knowledge of ML frameworks and libraries commonly used with SageMaker, such as PyTorch, TensorFlow, scikit-learn, or XGBoost
Knowledge of MLOps concepts, including CI/CD for ML, model versioning, monitoring, and retraining
Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements
Bachelor's degree in Computer Science, Engineering, or Data Science
Ability to obtain an AWS Certification, such as AWS Machine Learning – Specialty or AWS Solutions Architect – Associate, within 3 months of start date
Preferred
Experience implementing production MLOps pipelines using SageMaker Pipelines, Step Functions, or CI/CD tools
Experience supporting FedRAMP or ATO-driven cloud environments
Experience operationalizing models developed by data scientists or research teams
Experience working with OpenAI models or APIs, including integrating large language models into applications, building prompt-based workflows, or supporting GenAI use cases
Experience working in Agile or DevSecOps teams
Knowledge of GenAI or foundation model workflows using SageMaker, such as JumpStart, managed foundation models, or custom LLM deployments
Knowledge of IAM, VPC networking, encryption, and security controls for ML workloads in regulated environments
Benefits
Health, life, disability, financial, and retirement benefits
Paid leave
Professional development
Tuition assistance
Work-life programs
Dependent care
Recognition awards program
Company
Booz Allen Hamilton
Booz Allen Hamilton is a consulting firm that specializes in analytics, technology, and engineering.
10001+ employees
Funding
Current Stage
Public CompanyTotal Funding
$3.03B2025-03-11Post Ipo Debt· $650M
2023-08-01Post Ipo Debt· $650M
2020-08-13Post Ipo Debt· $700M
Leadership Team
Matthew Calderone
Chief Financial Officer and Executive Vice President
Kristine Anderson
Chief Operating Officer
Recent News
WSJ.com: US Business
2026-01-24
Benzinga.com
2026-01-23
2026-01-23
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