Platform Engineer

• 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
• What Success Looks Like (First 6–12 Months)
• Independent Ownership: Within your first 90 days you’ve shipped an infrastructure change through the full path — module, plan review, apply, monitoring — and by six months you own a Bedrock component (a Redstone stack, a pipeline family, or a tooling area) that teammates come to you about
• Terragrunt Modules Contributed: You’ve authored or refactored reusable OpenTofu/Terragrunt modules that pass review, follow the team’s conventions, and are adopted in stacks beyond the one you built them for
• Pipelines Measurably Better: Something a product engineering team can name got easier because of your Jenkins work — faster builds or deploys, fewer flaky failures, or quicker recovery — and you can show the before and after
• Trusted On-Call: You’re a full member of the rotation, your incident handoffs are clear, and the follow-ups you own land as durable fixes with written learnings rather than repeat pages
• Lifting Newer Engineers: Your reviews and docs are good enough that a newer engineer or co-op has learned part of the platform from them, and you’ve paired with or onboarded at least one
• Infrastructure as Code: Design, build, and maintain production cloud resources on AWS (EC2, ECS, S3, IAM) using OpenTofu and Terragrunt
• Pipeline Management: Own and improve Jenkins CI/CD pipelines, making it easier and faster for product engineering teams to deploy
• Automation Development: Develop internal developer tooling and automation scripts in Python to replace manual operational tasks
• Observability & Monitoring: Extend Datadog dashboards and monitors to track key service health and ensure alerts are actionable
• Container Operations: Work with Docker containerization to build, maintain, and run images and services
• Team Collaboration: Participate in sprint ceremonies, conduct constructive code reviews, handle on-call rotations, and help onboard newer engineers

Benefits

• Healthcare, dental, and vision: We cover 100% of Health, Dental, and Vision premiums for employees and their immediate families with multiple plan options available
• Wellness and relaxation: We want you to decompress and relax in a way that is best for you. From a Peloton membership to rock climbing, to massages, we’ll cover some of your costs
• Unlimited PTO: We recognize that our team works hard and ask that you take time when you need it
• Training and development: Attend conferences, classes, and trainings to hone your skills- 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