Senior Platform Engineer

Role overview Work as a senior platform engineer on a forward-deployed team building AI applications that help users understand and act on complex Naval engineering records. The role owns the systems and processes that move applications from source code into secure, production-ready environments, spanning release workflows, CI/CD pipelines, containers, Kubernetes, cloud infrastructure, and production troubleshooting.

Responsibilities - Own and improve end-to-end release workflows for AI applications, from container image build through production-ready release packages. - Build, publish, and maintain container images, manage dependency updates, and address or document vulnerabilities. - Develop and maintain CI/CD pipelines using GitHub Actions, GitHub runners, and GitLab workflows. - Configure, deploy, scale, and maintain production applications running in Kubernetes, including Zarf packages and declarative deployment artifacts. - Support deployment and troubleshooting of AI and GPU-enabled workloads. - Investigate data-ingestion and production issues across application code, infrastructure, system access, and deployment configuration. - Partner with application engineers and platform teams to plan deployments, resolve issues, and improve delivery practices.

Requirements - Significant experience deploying and maintaining production applications in Kubernetes. - Experience with Docker, container registries, and container-image lifecycle management. - Experience building CI/CD pipelines with GitHub Actions, GitLab CI, or comparable tools. - Experience deploying and operating workloads in AWS or a comparable cloud, plus Python proficiency and shell scripting familiarity. - Experience troubleshooting across application code, infrastructure, networking, access, and deployment configuration. - Familiarity with vulnerability remediation, dependency management, and container-security practices. - Ability to independently own complex technical work, anticipate risks and dependencies, and collaborate across engineering teams. - US citizenship and eligibility to apply for a security clearance or an active Top Secret/SCI clearance.

Nice to have - Experience with Zarf, declarative deployments, and infrastructure as code. - Experience deploying AI, machine learning, or GPU-enabled applications. - Familiarity with GPU scheduling and troubleshooting in Kubernetes, NVIDIA GPU Operator, or Chainguard images. - Experience with security automation, container, API, or cloud security. - Experience supporting production under a DoD Authority to Operate, DoD 8570 IAT II certification, or Agile remote engineering experience.

Benefits and work setup - Remote within the United States with occasional travel, typically one customer onsite and one to two company events per year. - Compensation range of $148,750 to $201,250 USD based on experience.