Platform Engineer II

Paperless Parts•Boston, MA

45d•$124,000 - $168,000•Hybrid

About The Position

Paperless Parts is looking for a Platform Engineer II to join Bedrock, the platform engineering team that builds and runs the infrastructure behind our SaaS platform for manufacturing shops. You will own the delivery of well-scoped infrastructure projects and system components end to end, helping manage cloud resources as code and improving how our engineering teams build, test, and ship software. This mid-level role is the perfect foundation for growth toward a Senior Platform Engineer, allowing you to take on real ownership of production infrastructure. You will participate fully in team operations, help onboard newer engineers, and shape how AI-assisted tooling accelerates our software development lifecycle.

Requirements

Hands-on experience managing production cloud infrastructure on AWS (compute, networking, IAM, storage).
Proficiency in Python or Bash with the ability to write clear, tested, and maintainable automation tooling.
Demonstrated capability working with infrastructure as code using Terraform or OpenTofu.
Solid Linux/Unix fundamentals and hands-on experience building, running, and troubleshooting Docker images and containerized services.
Experience building or maintaining continuous integration and deployment pipelines using tools like Jenkins, GitHub Actions, or GitLab CI.
Willingness to work in a hybrid environment in Boston, MA.
US Citizenship or Green Card Holder (due to US Export Control Laws).

Nice To Haves

Experience with Terragrunt.
Solid fundamentals working with Kubernetes containers in a Linux/Unix environment.
AWS GovCloud, FedRAMP, or SOC 2 exposure.
Regular use of AI coding assistants in infrastructure work, with judgment about when to trust the output.
Internal tools or self-service workflows adopted by other engineering teams.

Responsibilities

Design, build, and maintain production cloud resources on AWS (EC2, ECS, S3, IAM) using OpenTofu and Terragrunt.
Own and improve Jenkins CI/CD pipelines, making it easier and faster for product engineering teams to deploy.
Develop internal developer tooling and automation scripts in Python to replace manual operational tasks.
Extend Datadog dashboards and monitors to track key service health and ensure alerts are actionable.
Work with Docker containerization to build, maintain, and run images and services.
Participate in sprint ceremonies, conduct constructive code reviews, handle on-call rotations, and help onboard newer engineers.