Remote Platform Engineer — Cloud Infra & Kubernetes

United States Digital Space LLC; United States; Remote; USD 117,000 - 146,000; Full time

Benefits offered by this job

Healthcare

Retirement plan

Paid time off

Parental leave

Job summary

the company is seeking a Software Engineer, Platform Engineering (L2) to help build and operate backend services at scale in a remote-first team.

You will work on a dual-cloud stack (AWS and Azure), with Kubernetes, Terraform, and production code to keep distributed systems healthy under real production load. You’ll collaborate with senior engineers, learn AI-assisted tooling, and participate in scalable deployment workflows.

Qualifications

• 1-2+ years of professional software engineering experience, including some exposure to building or operating backend services using Kubernetes.
• Experience with AI-assisted development tools (e.g., Claude Code).
• Exposure to GitOps workflows (e.g., ArgoCD) and CI/CD pipelines.
• Working knowledge of Shell, Terraform, YAML, or Go (Golang).
• Experience with cloud environments (AWS/Azure).
• Familiarity with Terraform or similar IaC tools.
• Understanding of distributed datastores, caching, or event streaming.
• Solid CS fundamentals and data structures.

Responsibilities

• Design, build, and operate services and automations for Kubernetes clusters at scale.
• Participate in code reviews and testing standards.
• Support cloud configurations using Terraform and improve observability.
• Promote clean architectural practices and flag tech debt.
• Seek feedback, participate in sprint planning, and grow into a senior role.

Skills

Kubernetes

Terraform

Go

Shell

YAML

AWS

Azure

CI/CD

ArgoCD

Distributed systems

Canary deployments

Networking basics

Tools

Terraform

GitOps

Job description

the company is seeking a Software Engineer, Platform Engineering (L2) to help build and operate backend services at scale in a remote-first team.

You will work on a dual-cloud stack (AWS and Azure), with Kubernetes, Terraform, and production code to keep distributed systems healthy under real production load. You’ll collaborate with senior engineers, learn AI-assisted tooling, and participate in scalable deployment workflows.