Role overview

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.

Core requirements

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 DevOps 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

Preferred experience

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
OpenTelemetry, 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