
Software Architect –Automotive Inverters
- Gaydon, Warwickshire
- Permanent
- Full-time
- Define, lead, and evolve the role of Inverter Software Architecture for embedded control systems.
- Architect scalable, modular software platforms for motor control, diagnostics, and power electronics management.
- Ensure end-to-end compliance with AUTOSAR Classic and Adaptive environments, including configuration, integration, and middleware strategies.
- Coordinate interface definitions and abstraction layers between hardware, software, and vehicle domains.
- Implement and validate functional safety (ISO 26262) strategies and requirements through software architecture design.
- Conduct technical reviews, safety analyses, and performance assessments in collaboration with hardware, systems, and validation teams.
- Provide technical leadership across the software organization, mentoring engineers on design patterns, code structure, and safety standards.
- Work directly with OEM and Tier-1 stakeholders to define requirements, support integration, and align software architectures with platform goals.
- Contribute to innovation in SiC-based architectures, multi-phase inverter control, and next-gen fault detection strategies.
- Bachelor’s or master’s in electrical engineering, Computer Engineering, or related discipline.
- 7+ years’ experience in automotive embedded software architecture, focused on inverter systems and AUTOSAR environments.
- Expert-level proficiency in C/C++, MATLAB/Simulink, and model-based development workflows.
- In-depth knowledge of motor control algorithms, PWM strategies, and inverter signal processing.
- Experience with RTOS, CAN, SPI, and other automotive communication protocols.
- Hands-on involvement in safety lifecycle tasks, software safety concepts, and cybersecurity planning.
- AUTOSAR Classic and Adaptive toolchain experience, including MCAL and BSW configuration.
- Knowledge of battery management systems (BMS) and high-voltage architecture integration.
- Familiarity with HIL platforms and simulation-based architecture verification.
- Exposure to AI/ML frameworks for fault prediction or motor optimization.