Senior Software Architect – AI-Driven Infra & Tests

General Motors; Milford Charter Township (MI); Hybrid; USD 140.000 - 190.000; Vollzeit

Zusammenfassung

General Motors seeks a Senior Software Architect to define infrastructure software requirements, translate ECU-level requirements into deployable Solution and POD specifications, and build automated tests. This role leads across requirements, architecture, and verification, partnering with system engineers and software teams to ensure solutions are clear, testable, scalable, and ready for deployment.

Strong use of AI and LLM tools to accelerate design, improve requirements and test quality, and

Qualifikationen

• Bachelor's degree in Computer Science, Software Engineering, Electrical/Computer Engineering, or related field.

Aufgaben

• Lead technical direction for infrastructure areas (Communications, Controller Safety, Cybersecurity, Data Management, Diagnostics, Programming, Moding).
• Break ECU-level requirements into clear, testable Solution and POD requirements.
• Create Gherkin scenarios and develop reusable C++ and Python-based test automation.
• Drive defect triage, root cause analysis, and continuous improvement across requirements, software, and validation.
• Improve traceability, quality, and productivity through modern tooling, CI/CD, and AI-enabled engineering workflows.
• Mentor engineers in requirements authoring, automation, AUTOSAR, diagnostics, and testing best practices.

Kenntnisse

C++

Python

Embedded software

AI/LLM tools

CI/CD

AUTOSAR

CAN/LIN/Ethernet

Ausbildung

Bachelor's degree in CS/Software Engineering or related field

Tools

AUTOSAR Classic

HIL systems

Bench automation

Some/IP/DDS/REST

Jobbeschreibung

General Motors seeks a Senior Software Architect to define infrastructure software requirements, translate ECU-level requirements into deployable Solution and POD specifications, and build automated tests. This role leads across requirements, architecture, and verification, partnering with system engineers and software teams to ensure solutions are clear, testable, scalable, and ready for deployment.

Strong use of AI and LLM tools to accelerate design, improve requirements and test quality, and