Cloud Platform Engineer (DevOps, AI/ML Workloads)

This is a platform engineering seat, not a data science seat. The models are somebody else’s problem. Your problem is the environment they run in: the accounts, the pipelines, the identity boundaries, the container platform, and the automation that keeps all of it reproducible from one deployment to the next. The work sits inside a classified facility on a national security mission, so it moves at the pace security reviews allow. Engineers who thrive here are the ones who treat a constraint as a design input rather than an obstacle, and who would rather write the automation once than run the manual fix twice.

WHAT YOU WILL DO

• Build the platform. Stand up and operate the AWS environment that hosts mission workloads, including compute, storage, networking, and the container or orchestration layer those workloads depend on.
• Ship infrastructure as code. Write and maintain Terraform, CloudFormation, or CDK so environments are consistent, reviewable, and rebuildable rather than hand-tuned.
• Own the pipelines. Design and maintain CI/CD for both application and infrastructure changes, with automated testing, artifact management, and security scanning built into the path to production.
• Enforce identity and least privilege. Design IAM roles, policies, and federation patterns that give teams what they need and nothing beyond it.
• Support AI/ML workloads as a platform customer. Provision and tune the compute, storage, and pipeline capacity that model training and inference require, and keep it observable.
• Instrument everything. Build logging, metrics, alerting, and dashboards so failures announce themselves before a mission user reports them.
• Document what you build. Maintain runbooks, architecture diagrams, and decision records that hold up when the next engineer inherits the environment., All work occurs on-site within a classified facility in Northern Virginia. Remote and hybrid arrangements are not available for this seat. Because the polygraph requirement narrows the candidate pool sharply, D9Tech maintains an ongoing pipeline for this skill set. Cleared engineers are encouraged to apply even when no billet is posted, so that we can move immediately when one opens.

• Active Top Secret / SCI clearance with a current counterintelligence (CI) polygraph. This is the binding requirement on this seat.
• U.S. citizenship.
• Hands-on AWS engineering depth across compute, storage, VPC networking, and IAM.
• Infrastructure as code proficiency with Terraform, CloudFormation, or AWS CDK.
• CI/CD pipeline experience using tools such as GitLab CI, Jenkins, GitHub Actions, or the AWS CodePipeline toolchain.
• Containers and orchestration: Docker plus Kubernetes, EKS, or an equivalent platform.
• Scripting and automation in Python, Bash, or Go.
• Willingness and ability to work on-site in a SCIF in Northern Virginia., * AWS GovCloud or classified region experience.
• Experience supporting ML or GenAI workloads on AWS, including SageMaker, Bedrock, or GPU-backed compute.
• AWS certification such as Solutions Architect Associate or Professional, DevOps Engineer Professional, or Security Specialty.
• CompTIA Security+ (Sec+ CE) or an equivalent DoD 8140 baseline certification.
• Familiarity with NIST SP 800-53, RMF, and the ATO lifecycle.
• Prior delivery on a Federal, Department of Defense, or Intelligence Community program.

D9Tech Resources is a Service-Disabled Veteran-Owned Small Business and SBA 8(a) participant delivering cleared cloud, cybersecurity, network, data, and AI engineering to Federal and Department of Defense customers. Bench engineers are interviewed, verified, and kept ready, so that when a billet opens we place a known quantity instead of starting a search.