Senior Software Engineer - Infrastructure

New
B
Boundless Networks, Inc.Decentralized Computing
United States; globalFull-TimeSenior
Salary not disclosed
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Job Details

Experience
5+ years
Required Skills
AWSDockerPythonBashGCPKubernetesTypeScriptGoLinuxTerraformAnsible

Requirements

  • 5+ years of infrastructure/DevOps experience operating large-scale production systems
  • Deep expertise in Kubernetes, Docker, and container orchestration at scale
  • Strong proficiency with at least one major cloud platform (AWS/GCP)
  • Experience with multi-region and auto-scaling architectures on cloud platforms
  • Proficiency in infrastructure-as-code tools (Terraform, Ansible, Pulumi)
  • Strong Linux systems administration skills
  • Experience releasing complex software, including building and packaging Docker images, binaries, and maintaining distribution channels
  • Track record of managing mission-critical, high-throughput systems
  • Strong infrastructure-as-code background in heterogeneous environments
  • Proficiency in at least one common scripting or programming language (Python, Bash, TypeScript, Go, etc.)
  • Public GitHub profile included in application
  • GitHub profile demonstrating a minimum of 1 year of activity/history

Responsibilities

  • Build and deploy the computational infrastructure that powers Boundless, including compliance infrastructure for onchain finance and the world's largest decentralized proving network
  • Architect highly available, auto-scaling infrastructure across multiple regions and cloud providers (AWS, GCP)
  • Meet reliability and compliance guarantees for a managed financial service
  • Build infrastructure patterns for multi-tenant deployments across any public blockchain with isolation and security
  • Own deployment pipelines and release schedules for customer-facing environments
  • Ensure zero-downtime upgrades and safe rollouts across production tenants
  • Implement strategies to minimize infrastructure costs while maintaining performance
  • Manage spot instances, workload placement between on-prem and cloud, and resource scheduling
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