General Motors
Senior Software Engineer - Platform
Warren, Michigan, United States of America +1 · Hybrid · Senior · Full-time · Posted Jun 26, 2026
- Location
- Warren, Michigan, United States of America
Austin, Texas, United States of America - Experience
- 5+ years of professional software engineering, systems engineering, or platform support experience.
- Education
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field.
- Visa sponsorship
- GM does not provide immigration-related sponsorship for this role; applicants who need GM immigration sponsorship now or in the future should not apply.
About the job
Designs, supports, and modernizes enterprise applications and integrations for GM’s Global Physical Security and Medical portfolio, including cloud delivery, operational reliability, and secure AI capabilities.
What you'll do
- Build, maintain, and migrate applications and platform services; automate deployments and support CI/CD pipelines.
- Monitor and secure platforms, manage recovery procedures, troubleshoot incidents, and improve reliability and documentation.
- Identify and develop practical AI and intelligent automation solutions; evaluate technologies and mentor engineers.
What they ask for
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field.
- 5+ years of professional software engineering, systems engineering, or platform support experience.
- Strong scripting and automation experience; hands-on experience with Terraform, GitHub, Linux, Windows Server, and SSO/SAML.
- Experience with cloud platforms, CI/CD, deployment tooling, containerized applications, databases, and Linux administration.
Nice to have
- Experience with BrowserStack, OTEL, or DataDog.
- Experience with AI-enabled engineering tools, MCP-style integrations, or applying AI and LLM capabilities to operational workflows.
Tools
Bash, Python, Java, Terraform, GitHub, Linux, Windows Server, AWS
AI focus
Identify AI and intelligent automation opportunities; develop agentic AI solutions and apply AI/LLM capabilities to operational workflows, analytics, and decision support, with practical, secure, and responsible use.
Model-written summary · the original posting is authoritative