Staff Network Software Engineer — AV Hybrid Infra & Cloud

General Motors; Austin (TX); On-site; USD 140,000 - 210,000; Full time

Job summary

General Motors is seeking a Staff/Senior Software Engineer – Networking to design, build, and operate production network services for the AV Core Infrastructure. You will work across on-prem and cloud environments (GCP), delivering scalable, secure, and observable networking capabilities with a strong emphasis on automation and reliability.

You will apply distributed systems, API design, and CI/CD practices to reduce operational toil while ensuring high performance and data integrity for

Qualifications

• Experience building and operating production network services in Go and Python.
• Strong networking fundamentals including routing, switching, TCP/IP, DNS, data center networking, and BGP.
• Experience with distributed systems, APIs, concurrency, automated testing, CI/CD, and production operations.
• Familiarity with Site Reliability Engineering (SRE) practices and incident response.

Responsibilities

• Design, build, test, deploy, and maintain production network services and automation.
• Develop APIs, controllers, integrations, and tools for network provisioning, configuration, validation, and lifecycle management.
• Define, monitor, and improve SLOs for network services and ensure security, performance, and reliability.
• Lead or mentor engineers on complex projects while contributing as an IC.

Skills

Go

Python

Distributed systems

SRE practices

Linux

Networking fundamentals

GCP networking

Job description

General Motors is seeking a Staff/Senior Software Engineer – Networking to design, build, and operate production network services for the AV Core Infrastructure. You will work across on-prem and cloud environments (GCP), delivering scalable, secure, and observable networking capabilities with a strong emphasis on automation and reliability.

You will apply distributed systems, API design, and CI/CD practices to reduce operational toil while ensuring high performance and data integrity for