Senior Software Architect - Mechatronic Infrastructure

The Role  

We are seeking a Senior Software Architect to define infrastructure software requirements, translate ECU-level requirements into deployable Solution and POD requirements, and build the automated tests that validate them. 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 streamline engineering workflows is a key differentiator. 

What You’ll Do  

• Lead technical direction for infrastructure areas such as Communications, Controller Safety, Cybersecurity, Data Management, Diagnostics, Programming, and 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. 

Required Qualifications  

• Bachelor’s degree in Computer Science, Software Engineering, Electrical/Computer Engineering, or a related field, or equivalent experience. 

• 5+ years of relevant software experience, including test automation for embedded or distributed systems. 

• Strong C++ and Python skills for test automation, tooling, or framework development. 

• Working knowledge of AUTOSAR Classic or similar embedded platforms. 

• Experience with CAN, LIN, Ethernet, UDS, and DoIP. 

• Strong understanding of software development lifecycle, testing methods, and CI/CD. 

• Proven ability to turn complex behavior into testable requirements and drive issues to closure across cross-functional teams. 

• Experience using AI or LLM tools to improve engineering efficiency, design quality, or process flow. 

Preferred Qualifications  

• Master’s degree in a related field. 

• 7–10 years of experience in embedded, infrastructure, or automotive software, ideally in SDV or similarly scaled architectures. 

• Experience with HIL systems, bench automation, vehicle testing, and service-oriented communication such as SOME/IP, DDS, or REST. 

• Experience extending automation frameworks, dashboards, and metrics. 

• Experience leading technical initiatives and mentoring engineers. 

• Strong practical use of AI and LLM tools for requirements generation, test creation, debugging, and faster development cycles.