Diagnostics Systems Engineer

Diagnostic Requirements

Define and establish Diagnostic Common data requirements based on analysis of field issues and diagnostic gap analysis.

Diagnostics Gap Analysis & Catalog Management

Conduct thorough Diagnostic Gap Analyses across vehicle features, Electronic Control Units (ECUs), and components. Maintain and continuously improve diagnostic requirements in collaboration with cross-functional system teams.

Agile Team Leadership

Participate in and lead SAFe Agile ceremonies, acting as a Scrum Master/Lead to organize daily stand-ups, backlog refinements, and sprint planning.

Workflow Automation & AI Integration

Drive innovation by developing Python automation scripts, utilities, and full-stack applications leveraging Large Language Models (LLMs) to automate diagnostic requirement generation and streamline tool integration.

Cross-Functional Collaboration

Support engineering teams in developing utilities and applications on the department's AI tools. Collaborate with Feature and Algorithm teams to compile, consolidate, and validate data collection requests.

Data Workflows

Design and implement workflows that empower systems engineering and AI teams to utilize diagnostic data and requirements effectively.

Qualifications

• Bachelor's degree in Electrical Engineering, Computer Engineering, Software Engineering, Data Science, or a related field.
• 3+ years of experience in automotive diagnostics, vehicle systems engineering, or data engineering roles.
• 2+ years of familiarity with in-vehicle communication protocols (e.g., CAN, LIN, Ethernet, UDS, OBD-II).
• 2+ years of proven experience in requirements management and systems engineering workflows.
• 2+ years of experience with programming/scripting languages (e.g., Python, JavaScript/TypeScript, Scala, Java) for data manipulation, workflow automation, or tool development.
• Even better, you may have… Master's degree in a relevant engineering or data science discipline.
• Experience developing full-stack web tools (e.g., React, Node.js, SQL/NoSQL databases) to automate engineering processes or provide analytical dashboards.
• Experience with cloud-based data platforms (e.g., Google Cloud Platform, BigQuery, AWS, Azure) and building data lakes.
• Experience with AI/Machine Learning concepts and model development, especially utilizing LLMs to solve engineering efficiency challenges.
• Experience working within a SAFe Agile framework and acting as a Scrum Lead or Product Owner.
• 3+ years of experience with data analysis, data validation, and developing complex SQL queries.
• Strong communication and collaboration skills to work effectively with diverse engineering, IT, and external supplier teams.
• Experience with Model-Based Systems Engineering (MBSE) and systems architecture tools (e.g., MagicDraw, Jama Connect, or IBM DOORS).
• Excellent analytical, problem-solving, and troubleshooting skills.