Platform Engineer

Paperless Parts

Boston, United States Posted September 20, 2026

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Hybrid Full-time Mid level
Salary Range

$124,000 - $168,000

Job Description

Join Paperless Parts, a leading SaaS platform for manufacturing shops, as a Platform Engineer II. In this mid-level role, you will own the delivery of infrastructure projects and system components, manage cloud resources as code, and improve the software development lifecycle. You will have the opportunity for growth towards a Senior Platform Engineer position and will participate fully in team operations, help onboard newer engineers, and shape AI-assisted tooling. Benefits include healthcare coverage, unlimited PTO, and training and development opportunities.

  • Conception, construction, and maintenance of production cloud resources on AWS using OpenTofu and Terragrunt.
  • Ownership and enhancement of Jenkins CI/CD pipelines to facilitate faster deployments for product engineering teams.
  • Development of internal developer tooling and automation scripts in Python to automate operational tasks.
  • Linux & Containers: Solid Linux/Unix fundamentals and hands-on experience building, running, and troubleshooting Docker images and containerized services
  • Automation Scripting: Proficiency in Python or Bash with the ability to write clear, tested, and maintainable automation tooling
  • Cloud Infrastructure: Hands-on experience managing production cloud infrastructure on AWS (compute, networking, IAM, storage)
  • Location: Willingness to work in a hybrid environment in Boston, MA
  • Infrastructure as Code: Demonstrated capability working with infrastructure as code using Terraform or OpenTofu
  • CI/CD Pipelines: Experience building or maintaining continuous integration and deployment pipelines using tools like Jenkins, GitHub Actions, or GitLab CI
  • Advanced IaC & Containers: Experience with Terragrunt and solid fundamentals working with Kubernetes containers in a Linux/Unix environment
  • Regulated Environments: AWS GovCloud, FedRAMP, or SOC 2 exposure
  • AI-Assisted Engineering: Regular use of AI coding assistants in infrastructure work, with judgment about when to trust the output
  • Developer Experience Tooling: Internal tools or self-service workflows adopted by other engineering teams
Required Skills
manufacturing software development Amazon Web Services Jenkins CI/CD Python Linux troubleshooting Docker Bash Terraform GitHub Actions GitLab CI Kubernetes
How to apply

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