System Design Engineer - AI & Automation, LIGHT

Responsibilities Cross-Disciplinary Automation: Design and implement AI workflows that bridge the gap between Systems Engineering and downstream disciplines (HW, SW, Mech) to ensure seamless requirements traceability and consistency.

Physics-Informed Modeling: Develop and deploy Physics-Informed Machine Learning (PIML) models to accelerate simulations in Mechanics and Electrotechnique.

AI-Enhanced System Engineering: Integrate AI-assisted coding, automated unit testing, and bug prediction tools into the software development pipeline in compliance with ASPICE standards.

Predictive Project Management: Build predictive analytics dashboards for Technical Project Managers to forecast resource bottlenecks, budget risks, and milestone delays using historical project data.

Standards & Compliance: Ensure all AI-automated processes and generated outputs adhere to ISO 26262 (Functional Safety) and ISO/SAE 21434 (Cybersecurity) requirements.

Toolchain Integration: Lead the integration of AI agents with existing toolchains, including PLM, ALM (Codebeamer), and MATLAB/Simulink.

Key competenciesTechnical Skills

AI and Machine Learning

• Generative AI & LLMs
• Predictive Modeling
• Computer Vision

Data Engineering and Management

• Data Pipeline Construction: Automating the flow of data into AI models.
• Data Quality Assurance: Cleaning and labeling datasets to ensure the AI isn't learning from "noise."

Process Automation & Integration (MLOps)

• Workflow Orchestration: Using tools to connect AI outputs to other R&D software (like ELNs or LIMS).
• Deployment: Ensuring the AI tools are accessible via user-friendly interfaces.

Programming & Scripting

• Python
• Javascript / Google Apps Script
• Google Docs / Sheets functions & automation
• HTTP rest API's

Tooling & ALM: ( Plus Knowledge)

• Codebeamer (Requirement Management Tool)
• Google Cloud Platform

Automation & Integration concepts

• AI & Data Handling:
• Basic to intermediate experience with AI tools, APIs, or AI agents
• Interest in applying AI to engineering processes

Soft Skills

• Strong communication and collaboration skills, including ability to translate technical AI capabilities into tangible benefits for the teams
• Ability to work autonomously and proactively
• Analytical mindset with strong problem-solving skills
• User-oriented mindset (training, support, feedback handling)
• Time Managment

Nice to Have

Experience with requirement traceability or compliance activities

Exposure to AI-assisted automation or low-code/no-code platforms

Physics-Informed Machine Learning (PIML)

Predictive Project Analytics

Understanding of system engineering lifecycle and deliverables

Aware About Automotive Industry And Embedded Systems.

Years of Experience 2 to 3 years experience in AI & tools development