AI-Powered Infotainment Quality Engineer

Ford; Dearborn (MI); Hybrid; USD 84,000 - 162,000; Full time

Benefits offered by this job

Medical benefits

Parental leave

Vehicle discount

Tuition assistance

Paid time off

Paid holidays

Job summary

Ford Motor Company in the United States seeks an experienced Quality Engineer to champion electrical, infotainment, and connectivity systems on future vehicle programs. You will work with engineers, suppliers, and cross-functional teams to build robustness from design through launch.

The role emphasizes FMEA/DFMEA, root-cause analysis, MBSE practices, and data-driven decision making using AI-powered analytics.

Qualifications

• Bachelor's degree in Electrical Engineering, Computer Engineering, Systems Engineering, Aerospace Engineering, or related discipline.
• 3–5 years of experience in automotive or electronics quality engineering.
• Experience with FMEA/DFMEA and root-cause analysis (e.g., 5-Why).
• Strong verbal and written communication; strong analytical skills.
• Familiarity with MBSE practices.

Responsibilities

• Conduct CPA with suppliers to ensure FMA docs and SCCAFs.
• Lead root-cause investigations with design engineers and suppliers; drive corrective actions.
• Audit quality deliverables against GPDS milestones and DVP&R to confirm launch readiness.
• Analyze quality and warranty data with AI analytics to identify trends and risks.
• Utilize AI tools with Jira, Jama Connect and FEDE to improve reviews and cross-team collaboration.

Skills

Problem solving

Analytical thinking

Communication

Cross-functional collaboration

Adaptability

Education

Bachelor's degree in Electrical/Computer/Systems/Aerospace Engineering

Tools

Jira

Jama Connect

FEDE

GSAR

MagicDraw

MBSE tools

AI-assisted DFMEA tools

Job description

Ford Motor Company in the United States seeks an experienced Quality Engineer to champion electrical, infotainment, and connectivity systems on future vehicle programs. You will work with engineers, suppliers, and cross-functional teams to build robustness from design through launch.

The role emphasizes FMEA/DFMEA, root-cause analysis, MBSE practices, and data-driven decision making using AI-powered analytics.