Enterprise Cybersecurity AI Infrastructure Engineer

Job Number: R0251567

Enterprise Cybersecurity AI Infrastructure Engineer
The Opportunity:

Are you technically inclined, intellectually curious, and adaptable, with a strong cyber-defense mindset? Do you thrive in a fast-paced, dynamic environment, seek to understand complex challenges, ask thoughtful questions, and look beyond the obvious to identify innovative and effective ways of working? Do you bring a security first perspective, analytical problem-solving skills, and curiosity along with aptitude to continuously evolve as threats, technologies, and mission needs change?

As a Cybersecurity AI Infrastructure Engineer, you will operate as a hands-on technical contributor responsible for building, scaling, and operationalizing for Booz Allen's Cyber Operations AI infrastructure platform, supporting training, evaluating, hosting, and serving of AI capabilities. In this role, you will lead key components of the platform, including Databricks for data and model delivery and GitHub with AWS for the deployment pathway for moving internal AI products into production.

You will streamline collaboration between development and operations, ensuring systems and workflows move efficiently, work with AI/ML engineers, data scientists, and security operators, to transform security telemetry, threat intelligence, and analyst workflows into reliable, scalable pipelines and services. You will also build and operate CI/CD and DevSecOps for these products, including GitHub Actions, infrastructure as code, identity, secrets, and least-privilege access in Unity Catalog.

You will perform design and code reviews, set technical direction for platform work, and turn researcher and analyst needs into reusable infrastructure, leverage strong software engineering and communication skills to assess platform problems, align technical and non-technical stakeholders, and drive decisions to closure in support of Booz Allen's cyber operations and mission platforms.

What You'll Work On:

• Partner with AI and 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 to land security telemetry and threat intelligence including logs, endpoint, identity, cloud, and threat-intel sources into governed schemas analysts and models can use.

• Build model evaluation, validation, and serving paths, including experiment tracking, regression checks, and safe rollout and rollback, so models reach operations with a measured quality bar.

• 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 to keep non-production identities off production data.

• Own infrastructure as code for catalogs, permissions, and deployment such as Terraform or Terragrunt, and Databricks Asset Bundles so every environment is repeatable.

• Use coding assistants to accelerate delivery, and review generated infrastructure, pipeline, and application changes before they merge.

You Have:

• 5+ years of experience software engineering 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 like AWS and Databricks and building CI/CD in GitHub Actions with AWS integration, including IAM, OIDC federation, and Secrets Manager
• Experience in Python and SQL, and working with infrastructure as code such as Terraform or Terragrunt while also utilizing 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
• HS diploma or GED

Nice If You Have:

• 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 across 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 incorporate into analyst workflows

• IT, cloud, or security Certification such as AWS, Databricks, CKA, CKAD, CISSP, or an AI security Certification

Clearance:

Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information.

Compensation

At Booz Allen, we celebrate your contributions, provide you with opportunities and choices, and support your total well-being. Our offerings include health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, work-life programs, and dependent care. Our recognition awards program acknowledges employees for exceptional performance and superior demonstration of our values. Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible to participate in Booz Allen's benefit programs. Individuals that do not meet the threshold are only eligible for select offerings, not inclusive of health benefits. We encourage you to learn more about our total benefits by visiting the Resource page on our Careers site and reviewing Our Employee Benefits page.

Salary at Booz Allen is determined by various factors, including but not limited to location, the individual's particular combination of education, knowledge, skills, competencies, and experience, as well as contract-specific affordability and organizational requirements. The projected compensation range for this position is $77,600.00 to $176,000.00 (annualized USD). The estimate displayed represents the typical salary range for this position and is just one component of Booz Allen's total compensation package for employees. This posting will close within 90 days from the Posting Date.

Identity Statement

As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.

Candidate AI Usage Policy

AI is a part of our daily work at Booz Allen, and we are committed to the responsible and ethical use of AI tools. However, we want to ensure a fair candidate process based on your own skills and knowledge. As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with responses during interviews (whether in-person or virtual) is prohibited unless permission is explicitly provided .

Work Model
Our people-first culture prioritizes the benefits of collaboration. To support engagement and effective communication, employees working virtually are generally expected to have their cameras on during meetings.

• Remote : If this position is listed as remote, there may still be occasions when you are required to work in person at a Booz Allen or customer facility.
• Hybrid : If this position is listed as hybrid, you will be expected to work from a Booz Allen or customer facility, in alignment with your leadership's expectations and the needs of the role.
• Onsite : If this position is listed as onsite, work will primarily be performed full-time at a customer facility, where employees will collaborate directly with colleagues and customers as required by the role.

Commitment to Non-Discrimination

All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.