Sr Software Engineer, PLM Platform

This is a hands-on senior individual-contributor role supporting the technical layer around a Product Lifecycle Management (PLM) platform. The engineer will build and operate backend services, integrations, automation, and custom extensions that connect PLM with ERP, analytics, ECAD, and other downstream enterprise systems.

The ideal candidate is a production-minded backend engineer who can own solutions end-to-end—from architecture and coding through CI/CD, Kubernetes deployment, observability, and production support.

• 11+ years of experience building and supporting production backend software

• Strong expertise in modern backend development; C#/.NET is preferred

• Strong Java, Go, or Kotlin engineers are also acceptable if willing to work in C#/.NET

• Cloud-native engineering experience, preferably Microsoft Azure

• AWS or GCP experience is acceptable

• Hands-on experience with containers and Kubernetes
  , including real-world troubleshooting

• Strong API and enterprise-integration experience, including:

• REST APIs

• API pagination, retries, idempotency, and partial-failure handling

• OAuth 2.0 and OpenID Connect/OIDC

• Experience with relational and document data modeling

• Infrastructure-as-code and CI/CD ownership

• Bicep, Terraform, ARM, Azure Dev Ops Pipelines, or comparable tools

• Strong understanding of code-level design patterns and SOLID principles

• Automated testing, production telemetry, troubleshooting, and operational ownership

• Excellent written communication for design notes, runbooks, and engineering documentation

• Interest in product-engineering domains, including product definitions, BOMs, engineering changes, and release processes

• PLM, PDM, ERP, CAD, or engineering-systems background

• PTC Windchill experience is a strong plus, though PLM experience is not mandatory

• Azure Service Bus, Event Hubs, Event Grid, or other message-driven architecture experience

• Open Telemetry, Application Insights, Grafana, or related observability tooling

• Experience modernizing legacy applications while maintaining production stability

• Experience using AI-assisted engineering tools productively for development, debugging, testing, and documentation