Key Responsibilities

Problem Solving: Utilize AI-assisted and traditional debugging techniques to analyze complex hardware/software issues and drive them to resolution. Embedded SW Development: Develop & Test robust, safety-critical Embedded C code for various microcontrollers: In Basic Software (BSW), Hardware Abstraction Layers (HAL), low-level drivers (ADC, PWM, SPI, CAN, LIN), and Product specific Application SW. Powertrain Application: Implement software for high-voltage and electromechanical products—including Inverters, DC-DC Converters, Battery Management Systems (BMS), Thermal Management, and Smart Actuators—translating control laws and physical constraints into efficient code. AI & Innovation: Actively leverage Generative AI and Agentic AI tools to accelerate development, and optimize workflows, while applying LLM fundamentals to automate routine engineering tasks. Standard Compliance: Execute all development activities in strict adherence to automotive standards, including AUTOSAR architecture, ISO 26262 (Functional Safety), and ISO 21434 (Cybersecurity). System-Level Contribution: Collaborate with electrical, mechanical, and thermal engineers to define system constraints and ensure software optimizes the physics of the powertrain (e.g., cooling strategies, motor torque limits). Quality & KPIs: Maintain high standards for code quality (MISRA C compliance), documentation, and testing, ensuring all personal and team Key Performance Indicators (KPIs) are met or exceeded. Agile Collaboration: Work effectively within an Agile/Scrum framework, participating in daily stand-ups, sprint planning, and reviews to deliver incremental value. Cross-Functional Teamwork: Engage smoothly with cross-functional teams—including Requirements, System Engineering, and Testing/Validation—to ensure seamless integration and traceability from customer requirements to final product. Reporting: Provide clear, regular status reports to management regarding development progress, risks, and technical challenges.

Candidate Profile

Education: B. Sc. or M. Sc. in Mechatronics, Electrical Engineering, Electronics Engineering, Mechanical Engineering, Applied Physics, Aerospace Engineering, or a related field. Experience: 0–2 years of experience in embedded software development (internships and academic projects count). AI: Excellent Generative AI adoption, Agentic AI experience, and LLM fundamentals. Machine Learning is a plus Electrical Systems: Understanding of Power Electronics (Inverters, DC-DC converters) and Electric Motors. Knowledge of Control Theory: Automatic Control, Control Laws and modeling (Simulink/MATLAB). Mechanical Systems: Basic understanding of Mechanics, Electromechanics, and Thermodynamics (heat transfer/cooling systems) is a strong advantage. Programming: Strong proficiency in any programming language. Microcontrollers (is a plus): Deep understanding of microcontroller architecture (memory map, registers, interrupts, timers). Embedded Fundamentals (is a plus): Knowledge of RTOS concepts, Low-level Software, and Hardware Abstraction Layers (HAL). Automotive Standards (is a plus): Familiarity with AUTOSAR architecture and methodology) and Functional Safety ISO26262 is a plus. High problem solving skills, and debugging.