Enterprise Cybersecurity AI Infrastructure Engineer

Booz Allen Hamilton • McLean, VA

1d

About The Position

The Cybersecurity AI Infrastructure Engineer is a hands-on technical contributor responsible for building, scaling, and operationalizing Booz Allen’s Cyber Operations AI infrastructure platform to support training, evaluation, hosting, and serving of AI capabilities. The role leads key platform components, including Databricks for data and model delivery and GitHub with AWS for deploying internal AI products to production.

The engineer streamlines collaboration between development and operations and works with AI/ML engineers, data scientists, and security operators to turn security telemetry, threat intelligence, and analyst workflows into reliable, scalable pipelines and services. The role builds and operates CI/CD and DevSecOps capabilities, including GitHub Actions, infrastructure as code, identity and secrets management, and least-privilege access in Unity Catalog. It also includes conducting design and code reviews, setting technical direction, translating researcher and analyst needs into reusable infrastructure, and aligning technical and non-technical stakeholders to support Booz Allen’s cyber operations and mission platforms.

Requirements

• 5+ years of software engineering experience, including 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 deployment into production workflows.
• Experience with cloud platforms such as AWS and Databricks, and building CI/CD in GitHub Actions with AWS integration, including IAM, OIDC federation, and Secrets Manager.
• Experience with Python and SQL, infrastructure as code such as Terraform or Terragrunt, and coding agents.
• Experience building and maintaining data pipelines over large or sensitive datasets, including schema management and reproducible deployments.
• Experience owning platform work end to end, from technical design through production deployment and operational monitoring.
• Experience applying DevSecOps practices to delivery pipelines, including least-privilege access, secret handling, and automated security checks.
• Knowledge of cybersecurity operations or security telemetry.
• Ability to obtain a Secret clearance.
• High school diploma or GED.

Nice To Haves

• Experience with containerization such as Docker and container orchestration such as Kubernetes.
• Experience with Spark, distributed training, or orchestration frameworks including Ray or PyTorch Distributed.
• Experience with MLflow or an equivalent stack for experiment tracking, evaluation harnesses, and a model registry on Databricks.
• Experience implementing retrieval and agent infrastructure, including vector indexes, model endpoints, tool gateways, and evaluation loops.
• Experience with AWS beyond identity and secrets, including storage, networking, or private connectivity into Databricks.
• Experience operating platforms in sensitive or regulated environments, including FedRAMP, IL4, or IL5.
• Knowledge of secure-AI practices aligned to NIST AI RMF, OWASP LLM Top 10, and MITRE ATLAS.
• Knowledge of SIEM, SOAR, or threat-intelligence platforms and how models are incorporated into analyst workflows.
• IT, cloud, or security certification such as AWS, Databricks, CKA, CKAD, CISSP, or an AI security certification.

Responsibilities

• Partner with AI/ML engineers, data scientists, and SOC operators to turn modeling and analyst requirements into shared platform capabilities, including retrieval, scoring, and agent workflow design.
• Build, operate, and optimize the platform behind internal AI products, including platforms based on Databricks and AWS.
• Implement and scale data pipelines that bring security telemetry and threat intelligence—including logs, endpoint, identity, cloud, and threat-intelligence sources—into governed schemas for analysts and models.
• Build model evaluation, validation, and serving paths, including experiment tracking, regression checks, and safe rollout and rollback.
• Build and maintain GitHub Actions CI/CD for AI products, including self-hosted runners, AWS OIDC into IAM, Secrets Manager, pull-request environments, and production promotion.
• Implement DevSecOps controls, including dependency and secret scanning, infrastructure policy, service-principal isolation, and Unity Catalog grants that prevent non-production identities from accessing production data.
• Own infrastructure as code for catalogs, permissions, and deployments, using tools such as Terraform or Terragrunt and Databricks Asset Bundles.
• Use coding assistants to accelerate delivery and review generated infrastructure, pipeline, and application changes before they are merged.
• Perform design and code reviews, set technical direction for platform work, and translate researcher and analyst needs into reusable infrastructure.
• Assess platform problems, align technical and non-technical stakeholders, and drive decisions to closure.

Benefits

• Health, life, and disability benefits.
• Financial and retirement benefits.
• Paid leave.
• Professional development.
• Tuition assistance.
• Work-life programs.
• Dependent care.
• Recognition awards for exceptional performance and demonstration of company values.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: High school or GED