Senior Software Engineer – PLM Platform

Tangentia; United States; Remote; USD 170,000 - 210,000; Full time

Job summary

Tangentia in the United States is seeking a hands-on senior backend engineer to support a PLM platform. You will build and operate backend services, integrations, automation, and custom extensions connecting PLM with ERP, analytics, ECAD, and other enterprise systems.

You will own solutions end-to-end—from architecture and coding through CI/CD, Kubernetes deployment, observability, and production support, applying SOLID principles and robust testing.

Qualifications

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

Responsibilities

• Own backend architecture and implementation from design to production.
• Build and operate backend services and integrations.
• Own CI/CD pipelines and Kubernetes deployment.
• Ensure observability and production support.

Skills

Java

Go

Kotlin

C#.NET

Azure

AWS/GCP

Kubernetes

CI/CD

API design

OAuth 2.0 / OIDC

Data modeling

SOLID principles

Observability

Runbooks

Documentation

Tools

OpenTelemetry

Application Insights

Grafana

Terraform

Job description

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 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
• 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 Windchillexperience 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