Forward Model & Issue Resolution Quality Insights Supervisor

Ford Motor • Dearborn, MI

2d • Hybrid

About The Position

Ford’s Product Creation and Industrialization organization brings together vehicle, electric, digital, design, and manufacturing teams to develop vehicles, software, and customer experiences. This role supports Forward Model Quality and partners closely with system triage and issue-resolution teams to improve electronics and software quality and launch readiness.

The supervisor drives forward-model issues to verified closure, translates issue and field data into practical insights, and owns the definitions, data quality, dashboards, and reporting cadence used to assess triage, resolution, and forward-model quality. The role also helps system triage and issue-resolution teams organize and prioritize AI efforts, connect overlapping work, and adopt useful solutions. It supervises a small team that coaches engineers in practical AI use and supports pilots and hackathons. The position works across quality, engineering, triage leadership, and other partner teams to improve quality, efficiency, issue-resolution performance, and launch readiness.

This is a hybrid position requiring onsite work four or more days per week. It is leadership level 6, with a stated salary range of $150,000–$180,000. Visa sponsorship is not available; candidates must be legally authorized to work in the United States.

Requirements

• Bachelor’s degree in Software Engineering, Electrical Engineering, Computer Science, Data Science, Systems Engineering, Mechanical Engineering, or a related field.
• At least 5 years of experience in automotive systems, software, electronics, quality, systems engineering, product development, or a related technical discipline, including driving cross-functional projects or issues to completion.
• Demonstrated experience managing technical programs or projects, including scope, schedules, dependencies, risks, and status reporting.
• Experience defining metrics, building dashboards, and using data to track performance, identify trends, prioritize work, and improve issue-resolution outcomes.
• Experience supporting, deploying, or using AI-enabled or digital solutions to improve technical or business outcomes, and ability to translate operational problems into practical use cases.
• Working knowledge of vehicle electronics and software, including architecture, interfaces, diagnostics, failure modes, and system-level troubleshooting.
• Strong communication and collaboration skills, including the ability to drive accountability across cross-functional teams and clearly present status, metrics, and risks to leaders.
• Ability to lead or coordinate a small team, develop others, and deliver results through disciplined execution and influence.
• Legally authorized to work in the United States; employment eligibility will be verified at hire.

Nice To Haves

• Master’s degree in a technical, data, artificial intelligence, or management field, or a project management certification such as PMP.
• At least 7 years of experience in automotive electrical, electronic, software, systems, or quality engineering.
• Experience helping engineering teams identify, organize, and deliver AI, analytics, or automation ideas from concept through everyday use.
• Experience supervising a small technical team or leading work across a matrixed organization.
• Experience in forward-model or new-vehicle quality, including prototype builds, launch readiness, and rapid response to electrical and software quality concerns.
• Proficiency with dashboarding and data tools such as Power BI, Jira dashboards, SQL, or Python.
• Working familiarity with generative AI, machine learning, intelligent automation, evaluation methods, and responsible-AI controls, including human review before AI results influence engineering or quality decisions.
• Knowledge of Ford product-development and issue-management processes and tools, including AVBOM, WERS, AIMS, 8Ds, eFDVS, Jama, Engineering Sign Off, DFMEA, Six Sigma, Confluence, and Jira applications.
• Experience planning or running hackathons, pilots, or rapid experiments.
• Curiosity and a strong bias for practical application, experimentation, learning, and measurable improvement in engineering quality and efficiency.

Responsibilities

• Support rapid cross-functional response to emerging electronics and software issues during forward-model development, prototype and pre-production builds, launch, and early production.
• Track issues through containment and resolution, support launch-readiness reviews, and capture lessons learned for engineering.
• Drive forward-model electronics and software issues to verified closure ahead of key program milestones.
• Define and track forward-model quality measures, including issue burn-down to milestones, repeat issues, and 8D closure timing, and report launch readiness to leadership.
• Use insights from current and past models to inform design reviews, DFMEAs, test plans, and lessons learned to prevent repeat issues.
• Maintain a shared view of AI ideas and projects for system triage and issue-resolution teams, help set priorities, connect overlapping efforts, and keep work focused on operational needs.
• Help teams locate existing tools, data, and approved platforms, and connect them with AI, data, and cybersecurity contacts as needed.
• Supervise a small team that coaches engineers on practical AI use through hands-on sessions, office hours, and shared examples; capture and share reusable solutions.
• Drive electronics and software issues to closure by confirming ownership, setting next steps and due dates, removing blockers, and escalating at-risk issues.
• Hold teams accountable for timely containment, root cause, corrective action, and verified closure.
• Support system-level triage and troubleshooting using vehicle, system, and cross-feature knowledge; use AI tools to improve signal detection, evidence synthesis, issue routing, and prioritization.
• Own system-triage and issue-resolution metrics, including definitions, data sources, targets, dashboards, and reporting cadence.
• Track time to triage, time to resolution, issue aging, backlog, throughput, reopen rate, issue-intake quality, and AI adoption; identify trends and drive action.
• Analyze issue, warranty, and field data to identify recurring failure modes and systemic causes, and translate insights into practical actions for engineering and triage teams.
• Establish and maintain data standards, classification fields, and Jira hygiene so metrics are accurate, consistent, and trusted across teams.
• Execute and continuously improve issue intake, triage, escalation, reprioritization, closure, and learning processes; reinforce ownership, criteria, and decision paths, and integrate AI with traceability and human review.
• Support hackathons and small pilots addressing triage and issue-resolution problems; help evaluate outcomes, assign owners, and transition successful ideas into everyday tools.
• Prepare executive-ready reporting on metrics, insights, and risks, and align stakeholders across product, program, software, hardware, systems engineering, validation, manufacturing, service, and quality.

Benefits

• Immediate medical, dental, vision, and prescription drug coverage.
• Paid parental leave, new parent ramp-up programs, and subsidized back-up child care.
• Family-building benefits, including adoption and surrogacy expense reimbursement and fertility treatments.
• Vehicle discount program for employees and family members, and management leases.
• Tuition assistance.
• Employee resource groups.
• Paid time off for individual and team community service.
• Generous vacation time, sick/personal time, and paid holidays, including between Christmas Eve and New Year’s Day.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager