Senior Systems Engineer

Senior Systems Engineer Rail

Experience: 5 to 8 years

Domain: Rail / Locomotive / TCMS / Safety-Critical Systems

Role Overview

We are looking for a Senior Systems Engineer to analyze legacy locomotive product definitions and transform them into structured System Functional Specifications (SFS), Software Design Specifications (SDS), functional architecture and end-to-end traceability, while providing the engineering knowledge and rules required for an AI-assisted Systems Engineering solution.

Key Responsibilities

• Analyze legacy specifications, bit-level definitions, signals, interfaces, functional and software specifications.
• Convert legacy information into structured system requirements and SFS.
• Perform functional decomposition, allocation and interface analysis.
• Derive software requirements and SDS from approved system intent.
• Establish Source, SFS, Subsystem, SDS, Design and Verification traceability.
• Identify requirement gaps, ambiguity, duplication and inconsistencies.
• Support RAMS, safety, V&V and SIL-related activities.
• Define Rail Systems Engineering terminology, engineering rules and decision logic for AI use cases.
• Review and validate AI-generated requirements, SFS/SDS and traceability using source evidence.
• Establish the manual engineering baseline that will be used to benchmark the AI POC.

Required Systems Engineering Skills

• Strong Systems Engineering and Requirements Engineering experience.
• Rail/locomotive experience, preferably TCMS, propulsion, braking, doors, HVAC or train networks.
• Experience with DOORS/DOORS Next, Polarion, Enterprise Architect, Capella or similar tools.
• Strong understanding of V-model, functional architecture, allocation, interface management and V&V.
• Knowledge of ISO/IEC/IEEE 15288, ISO/IEC/IEEE 29148, INCOSE, IEC 62278 / EN 50126 and EN 50716 / IEC 62279.
• Experience with safety-critical / SIL-based systems preferred.

AI / Digital Engineering Exposure

• Understanding of Generative AI/LLMs and engineering applications.
• Exposure to RAG, prompt engineering and structured AI outputs.
• Understanding of AI-assisted requirements extraction and classification.
• Familiarity with knowledge graphs / engineering knowledge models.
• Ability to define AI validation criteria and human-in-the-loop workflows.
• Basic Python/scripting for engineering automation.

Education: Bachelor's/Master's degree in Electronics, Electrical, Computer Science, Control Systems, Systems Engineering or related discipline.