Software Engineer - Infrastructure

We're looking for a Software Engineer, Infrastructure to build the systems that power Capitol's platform — from cloud infrastructure and Kubernetes operations to CI/CD, observability, and internal tooling. You'll make a huge impact as part of a small team and have meaningful influence over how we scale and secure our infrastructure as we grow.

This is a high-ownership role. You'll be solving real problems across multi-tenant and single tenant environments serving enterprise and government clients.

Responsibilities

• Design, implement, and maintain scalable, secure, and compliant cloud infrastructure using Infrastructure as Code.
• Build and evolve CI/CD pipelines that improve developer velocity without sacrificing quality.
• Operate and improve Kubernetes-based systems, ensuring reliability across development and production environments.
• Drive observability — defining metrics, building dashboards, and making system health visible and actionable.
• Participate in on-call rotations, incident response, and postmortems.
• Contribute to compliance efforts (SOC 2 and beyond), translating controls into infrastructure reality.
• Build internal tooling and automation that makes engineers more productive.
• Collaborate proactively across teams, surfacing issues before they become blockers.
  
  

You May Be a Good Fit If You

• Have 7 years building and operating production infrastructure.
• Have led complex, cross-functional infrastructure projects end to end.
• Take ownership — you drive things to completion without waiting to be asked.
• Communicate clearly and proactively with both technical and non-technical stakeholders.
• Are fluent in Python, Go, Rust, or similar.
• Have deep knowledge of Kubernetes, Helm, OpenTelemetry, and at least one major cloud (GCP, Azure, or preferably AWS).
• Are experienced with Infrastructure as Code (Terraform, Pulumi, or similar).
• Have worked with security or compliance frameworks (SOC 2, FedRAMP, ISO 27001, or similar).
• Have enterprise software experience — you understand the constraints, expectations, and deployment patterns that come with large organizational clients.
• Have operated data or AI infrastructure at scale — experience running and supporting systems like Ray, Spark, or Temporal in production, where reliability and throughput directly impact model training or inference workloads.
  
  



Strong Candidates May Also Have

• Experience in early-stage startups or hyper-growth environments.
• Familiarity with multi-tenant SaaS architecture, data isolation, and GitOps patterns.
• Government or regulated industry experience.
• Contributions to open source infrastructure projects.