Senior Platform Engineer

Role Description:

We are seeking a Senior Platform Engineer to join a team developing AI applications that help users understand and act on complex Naval engineering records. Using a Forward Deployed Engineering model, our team works closely with mission users to understand how they work, identify friction in their daily tasks, and deliver functional improvements based on rapid feedback.

You will serve as the team’s primary platform engineering owner, responsible for the systems and processes that move our applications from source code into secure, production-ready environments. Your work will span release workflows, CI/CD pipelines, container images, Kubernetes configurations, cloud infrastructure, application deployments, and production troubleshooting.

This is a hands-on senior individual contributor role. You will independently own significant platform work, make technical decisions across systems, anticipate risks and dependencies, and collaborate with application engineers and platform teams across the company.

Responsibilities:

In this position, you will:

• Own and improve end-to-end release workflows for the team’s AI applications, from building container images through creating production-ready release packages.
• Build and publish container images, address or document vulnerabilities, manage dependency updates, and maintain release artifacts.
• Develop and maintain CI/CD pipelines using GitHub Actions, GitHub runners, and GitLab workflows.
• Configure, deploy, scale, and maintain production applications running in Kubernetes.
• Maintain Zarf packages, Kubernetes configurations, and other declarative deployment artifacts.
• Support the 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 technical issues, and improve delivery practices.
• Identify opportunities to make releases and deployments more secure, reliable, repeatable, and observable.
• Clearly communicate technical decisions, risks, and tradeoffs to both technical and nontechnical partners.
• Help diagnose and resolve high-impact production issues affecting mission users.

Travel Expectations:

Occasional travel is expected, typically including at least one customer onsite and one to two company events per year. Engineers may have additional opportunities to participate in customer visits and observe users working in their operational environment.

The listed responsibilities are not exhaustive and additional responsibilities may be assigned based on the evolving needs of the organization. We are seeking a dynamic individual who is able to adapt and take on new responsibilities as they arise.

Required Experience and Qualifications

• Significant experience deploying and maintaining production applications in Kubernetes.
• Experience with Docker, container registries, and container-image lifecycle management.
• Experience building or maintaining CI/CD pipelines using GitHub Actions, GitLab CI, or comparable tools.
• Experience deploying and operating workloads in AWS or comparable cloud environments.
• Proficiency in Python and familiarity with shell scripting.
• Experience troubleshooting problems 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, navigate ambiguity, and make sound decisions without requiring a fully prescribed solution.
• Ability to anticipate technical risks and dependencies and communicate them effectively.
• Strong collaboration skills and experience working across engineering teams.
• Eligibility to apply for a security clearance or an active Top Secret/SCI security clearance.

Preferred Experience and Qualifications

• Experience with Zarf.
• Experience deploying AI, machine-learning, or GPU-enabled applications.
• Familiarity with GPU scheduling, allocation, and troubleshooting in Kubernetes, including NVIDIA GPU Operator or related components.
• Familiarity with Chainguard images.
• Experience with declarative deployments and infrastructure as code.
• Experience supporting data-ingestion workflows.
• Experience with security automation, container security, API security, or cloud security.
• Experience supporting a production system operating under a Department of Defense Authority to Operate.
• Current DoD 8570 IAT II certification.
• Experience working in an Agile, remote engineering environment.