DevOps Engineer

Booz Allen Hamilton•McLean, VA

2d•$77,600 - $176,000•Hybrid

About The Position

Booz Allen is seeking a DevOps Engineer to help build next-generation cybersecurity products, modernize systems with artificial intelligence, and develop new capabilities. The role involves deploying and operating secure, reliable, and highly available software in cloud environments, supporting applications from pilots through critical production systems. The engineer will translate business and development-team requirements into automated platform solutions and collaborate with DevOps, platform engineering, development, and customer teams. The work calls for expertise in cloud technologies, networking, containers, Kubernetes, and CI/CD pipelines in a fast-paced Agile environment. The position supports enterprise software and AI-enabled applications, including deployments in customer-managed, self-hosted, and on-premises environments.

Requirements

At least 8 years of experience developing and implementing DevSecOps tools, automation, and processes.
At least 8 years of experience troubleshooting, triaging, and resolving complex CI/CD pipeline issues.
Experience designing, deploying, and maintaining cloud-native applications and infrastructure using Kubernetes, Docker, and CI/CD platforms such as Jenkins, GitHub Actions, or GitLab.
Experience developing, managing, hardening, and securing containerized workloads, including image security, vulnerability scanning, secrets management, and runtime security.
Experience deploying and supporting enterprise software in customer-managed, self-hosted, or on-premises environments.
Experience implementing DevSecOps security controls and automated compliance checks across the software delivery lifecycle.
Experience deploying and operationalizing AI-enabled applications in enterprise environments.
Experience collaborating with customer infrastructure, security, and platform engineering teams.
Secret clearance required.
Bachelor's degree required.
Excellent communication skills and ability to work independently and collaboratively in a fast-paced Agile environment.

Nice To Haves

Experience with cloud providers such as AWS or Microsoft Azure.
Experience integrating AI-driven capabilities into compliance, governance, risk management, or security workflows, including automated control validation, evidence collection, policy mapping, and compliance reporting.
Experience deploying and maintaining AI-powered solutions in self-hosted, on-premises, or customer-managed environments, including restricted-network or air-gapped environments.
Experience operationalizing AI applications in production, including health monitoring, logging, observability, performance troubleshooting, dependency management, and deployment lifecycle management.
Experience deploying Kubernetes-based applications using Helm or similar tools, including private container registries, persistent storage, network policies, and cluster-level security controls.
Experience working directly with customer security, infrastructure, and platform engineering teams to validate deployment architectures, resolve environment-specific issues, and meet enterprise security and compliance requirements.

Responsibilities

Develop and implement DevSecOps tools, automation, and processes to improve software delivery maturity, security posture, and operational reliability.
Troubleshoot, triage, and resolve CI/CD pipeline problems, including build and deployment failures, performance bottlenecks, and infrastructure issues.
Design, deploy, and maintain cloud-native applications and infrastructure using Kubernetes, Docker, and CI/CD platforms.
Develop, manage, harden, and secure containerized workloads, including container image security, vulnerability scanning, secrets management, and runtime security.
Deploy and support enterprise software in customer-managed, self-hosted, or on-premises environments; configure infrastructure dependencies, manage system integrations, and troubleshoot environment-specific issues.
Implement DevSecOps security controls and automated compliance checks throughout the software delivery lifecycle, including policy enforcement, vulnerability management, and audit evidence collection.
Deploy and operationalize AI-enabled applications in enterprise environments, managing application dependencies, securing model and data access, and supporting reliable, repeatable deployments.
Collaborate with customer infrastructure, security, and platform engineering teams to resolve deployment issues, meet security requirements, and support production adoption.
Work with DevOps and platform engineers and developers to deploy and operate secure, reliable, available applications from pilots to critical production systems.