Staff Cloud DX Engineer - CI/CD & AI‑Driven Workflows

United States Digital Space LLC; United States; Remote; USD 180,000 - 240,000; Full time

Job summary

United States Digital Space LLC. is seeking a Staff Engineer for the Cloud DX team. You will design, operate, and scale a production-grade delivery platform, contributing hands-on in Go and Python and leading cross-team initiatives across timezones.

You’ll champion progressive delivery, implement canary deployments and automated rollbacks, and embed AI-assisted workflows into the SDLC to boost engineering velocity and quality across the organization.

Qualifications

• Extensive CI/CD platform experience across admin and architecture.
• Hands-on Go production-grade development.
• Experience with cloud-native and Kubernetes-based platforms.

Responsibilities

• Own and evolve CI/CD architecture and the developer-facing experience.
• Drive improvements to pipeline reliability, speed, and predictability.
• Define paved paths that let product teams ship fast and safely.
• Own the delivery process end-to-end, from code merge to production.
• Champion progressive delivery practices: canary deployments & automated rollbacks.
• Build tooling that makes deployments observable, repeatable, and self-service.
• Own and evolve our Internal Developer Portal and the self-service experience around it.
• Partner with Cloud Platform teams on infrastructure while owning the developer-facing delivery.
• Embed AI tooling into delivery workflows for lasting productivity gains.

Skills

CI/CD ownership

Go development

Python development

Kubernetes

Cloud-native

Canary deployments

AI tooling

Platform engineering

Cross-team collab

RBAC OAuth security

Job description

United States Digital Space LLC. is seeking a Staff Engineer for the Cloud DX team. You will design, operate, and scale a production-grade delivery platform, contributing hands-on in Go and Python and leading cross-team initiatives across timezones.

You’ll champion progressive delivery, implement canary deployments and automated rollbacks, and embed AI-assisted workflows into the SDLC to boost engineering velocity and quality across the organization.