below marketmost similar roles pay hereabove market
This role pays less than
99%
of similar roles. Most pay
$148,875–$235,187
— the blue band above.
At the midpoint, this role pays about
$102k
versus about
$192k
for comparable roles.
Based on 240 similar postings.
Employer
About Booz Allen Hamilton
Booz Allen Hamilton is a management and technology consulting firm that provides analytics, digital, engineering, and cybersecurity solutions primarily to U.S. government agencies and commercial clients. Industry: Management & Technology Consulting
Booz Allen Hamilton currently has
1662 open roles
on FindRole.
Listed pay typically runs
$86,800–$198,000
across 904 roles with salary data.
The Enterprise Cybersecurity AI Infrastructure Engineer joins the Cyber Operations AI infrastructure team to build, scale, and operationalize a platform for training, evaluating, hosting, and serving AI capabilities. You will lead key components including Databricks for data and model delivery and GitHub with AWS for production deployment pathways. Daily responsibilities involve streamlining collaboration between development and operations, building CI/CD and DevSecOps pipelines, and transforming security telemetry and threat intelligence into scalable services. You will utilize Python, SQL, Terraform, Terragrunt, and Databricks Asset Bundles to manage infrastructure as code. The role requires implementing DevSecOps controls like secret scanning and least-privilege access within Unity Catalog. You will solve complex technical problems by turning researcher needs into reusable infrastructure to support cyber operations and mission platforms.
Build and scale the Cyber Operations AI infrastructure platform using Databricks and AWS.
Develop and optimize data pipelines to ingest security telemetry and threat intelligence into governed schemas.
Create model evaluation, validation, and serving paths including experiment tracking and safe rollouts.
Build and maintain CI/CD pipelines using GitHub Actions, Terraform, and Databricks Asset Bundles.
Implement DevSecOps controls such as secret scanning, identity management, and least-privilege access.
Translate researcher and analyst requirements into reusable infrastructure and shared platform capabilities.
Perform design and code reviews to ensure high-quality infrastructure and application changes.
Manage infrastructure as code for catalogs, permissions, and production deployment environments.
What we're looking for
2+ years of experience in software engineering building and operating production-scale machine learning infrastructure, data platforms, or distributed systems.
2+ years of experience creating and training agents and models for agentic AI, including tool calling, evaluation, and production deployment.
Experience with cloud platforms such as AWS and Databricks and building CI/CD in GitHub Actions with AWS integration.
Proficiency in Python and SQL and experience with infrastructure as code using Terraform or Terragrunt.
Experience building and maintaining data pipelines over large or sensitive datasets, including schema management and reproducible deployments.
Experience applying DevSecOps practices, including least-privilege access, secret handling, and automated security checks.
Knowledge of cybersecurity operations or security telemetry.
Ability to obtain a Secret clearance and a high school diploma or GED.