General Dynamics Information Technology is a global technology and professional services company focused on delivering consulting, technology, and mission services to U.S. government agencies. They are seeking a Principal DevSecOps / Platform Engineer to build and operate software factories, security automation platforms, and AI-enabled development environments for Department of Defense and Federal customers, emphasizing hands-on software development within a DevSecOps context.
Responsibilities:
- Design, develop, and maintain CI/CD pipelines for build, test, security scanning, and release across unclassified and classified environments
- Integrate and operate security scanning toolchains (SAST, SCA, container scanning, SBOM generation) as automated pipeline stages
- Use AI-assisted development workflows daily — code generation, automated testing, intelligent code review, and documentation — and champion their adoption across teams
- Contribute to the development of agentic AI capabilities including tool orchestration, prompt engineering, and workflow automation
- Build tooling and automation to support continuous Authority to Operate (cATO) processes, including automated evidence collection, compliance reporting, and policy enforcement
- Develop and maintain hardening pipeline templates that product teams consume for secure-by-default software delivery
- Support platform's security pipeline layer — build, test, and release process for software packages that include both application code and runtime platform components
- Implement and enforce software supply chain security controls (signing, provenance, artifact integrity)
- Troubleshoot build and deployment failures, support development teams consuming shared pipeline services
- Deploy and operate Kubernetes clusters (Big Bang / Iron Bank baseline) in classified (CUI/IL5) environments
- Deploy, configure, and support AI-powered development tools (GitLab Duo, LLM-based code assistants, agentic AI frameworks) for platform consumers and internal team use
- Support AI/ML platform infrastructure (model serving, GPU workloads, data pipelines) as part of the broader platform offering
- Stand up and maintain shared platform services: Harbor (container registry), Nexus (artifact repository), Vault (secrets management), ArgoCD (GitOps deployment)
- Implement Infrastructure-as-Code for environment provisioning, cluster lifecycle, and configuration management (Terraform, Ansible)
- Support multi-cluster management and hub/spoke deployment models — build in shared services, deploy into downstream accounts
- Configure and troubleshoot network connectivity, Zscaler integration, and Okta/SAML identity federation for platform consumers
- Contribute to platform evolution including self-service namespaces, developer onboarding, and golden-path templates
- Maintain and improve multiple production software factory environments serving diverse federal customers
- Contribute to runbooks, operational documentation, and incident response procedures
Requirements:
- 8 + years of related experience
- US Citizenship Required
- Education: Bachelor's degree and 8+ years experience. In lieu of degree 12+ years of hands-on experience
- 5+ years of related experience in Software Engineering, DevOps / DevSecOps technologies; 3+ years of hands on experience with Kubernetes
- Experience using AI-powered development tools (code assistants, LLM-based tooling, AI-augmented workflows) in daily engineering work — and enthusiasm for pushing their adoption forward
- Hands-on experience with CI/CD pipeline development — GitLab CI strongly preferred; Jenkins, GitHub Actions, or similar accepted
- Experience integrating security scanning tools into automated pipelines (SAST, DAST, SCA, container image scanning)
- Proficiency with Infrastructure as Code (Terraform and/or Ansible)
- Experience with containerization (Docker, Helm, OCI artifacts) and container registry management
- Strong Linux systems skills — administration, shell scripting, troubleshooting
- Solid understanding of Git-based workflows, branching strategies, and GitOps deployment patterns
- Experience working in or deploying to classified or air-gapped environments
- Ability to work across multiple concurrent projects with shifting priorities
- Strong written and verbal communication skills
- Security clearance level: Secret Clearance required to start
- Location: Remote with travel up to 10%
- Experience with Platform One / Big Bang, Iron Bank baselines, or DoD-hardened Kubernetes distributions
- Familiarity with DoD security and authorization frameworks (NIST 800-53, RMF, cATO, software factory authorization patterns)
- Knowledge of software supply chain security practices — artifact signing, attestation, and SBOM generation (e.g., Sigstore/Cosign, Syft, in-toto)
- Experience deploying or operating AI/ML infrastructure or AI development platforms in enterprise or air-gapped environments (model serving, GPU scheduling on K8s, enterprise code-assistant rollout)
- Experience supporting growth activities — contributing to proposals, RFI responses, or technical briefings, and engaging customers as a technical SME