Sr. Software Engineer, PLM Platform

• Hands-on experience in building and running production backend software.
• Strong command of code-level design patterns and SOLID principles, including repository, unit of work, dependency injection, factory, and strategy, with the judgment to know when a pattern is earning its keep and when it is overhead.
• Deep fluency in at least one modern backend language, and the ability to pick up another without drama. We build primarily in C#/.NET, so that is ideal. Strong Java, Go, or Kotlin engineers willing to work in C# are equally welcome.
• Production cloud experience. Azure preferred, AWS or GCP fine.
• Containers and Kubernetes in a real environment, including debugging a cluster you did not build
• Solid grasp of API integration: pagination, retries, idempotency, partial failure.
• Data modeling in relational and document stores.
• Working knowledge of OAuth 2.0 and OIDC. You should know what is in a token and what breaks when it is wrong.
• Comfortable owning infrastructure as code and pipelines rather than handing them off.
• Genuine interest in the engineering domain. Curiosity about how products are actually designed, revised, and released matters more here than it does on most teams.
• Clear writing. Design notes and runbooks are part of the job.
• Authorized to work in the United States for any employer without sponsorship
• PLM, PDM, ERP, or CAD systems experience. PTC Windchill is a strong plus, but we will teach it.
• Message-driven systems and their operational patterns:
  Azure Service Bus, Event Hubs, Event Grid.
• Open Telemetry, Application Insights, Grafana.
• Modernizing a legacy system while it stays in production.

A Bachelor’s or Master’s degree in any discipline from a recognized institution is acceptable.

• Design, build, and run backend services that deploy to Kubernetes on Azure.
• Build integrations between PLM and downstream systems, working with APIs you do not control and the failure modes that come with them.
• Work directly in the PLM platform: OData and REST interfaces, configuration, and custom Java extensions.
• Own your deployment path, including infrastructure as code, CI/CD pipelines, and Kubernetes manifests for what you build.
• Write automated tests as part of shipping, not as a follow-up.
• Instrument services so production problems are found in telemetry rather than by guessing.
• Review peers' code and hold a consistent bar.
• Work with product owners and engineering users to turn real problems into working software.