Jobs at Ford Motor Company

Lead modernization of the Variable Marketing & Incentives AI platform: define strategy, lead discovery and roadmaps, partner with dealers and engineering, leverage data and AI to optimize incentives, drive migration and operational controls, define success metrics, and deliver executive-aligned materials to ensure measurable business impact.

Lead Ford's battery pack manufacturing network, building greenfield plants and organization. Own SQDC (Safety, Quality, Delivery, Cost), launch execution, throughput, cost optimization, financial planning, and talent development across multiple facilities while ensuring cleanroom, electrochemical, and high-voltage process integrity.

Lead technical scoping and configuration of grid-scale and commercial BESS projects, perform system sizing and performance modeling, develop technical financial models (LCOS, NPV), draft technical contract exhibits, ensure safety and compliance (UL 9540A, NFPA 855), support certification and market interconnection, and align cross-functionally between sales, engineering, and customers.

Lead the architecture and implementation of scalable, distributed data and AI platforms on GCP. Design real-time and batch pipelines, integrate LLMs and vector search, define data models and API standards, optimize cloud infrastructure, enforce CI/CD and observability, and mentor senior engineers to drive product-led AI solutions at scale.

Provide regulatory legal advice on the Motor Vehicle Safety Act and FMVSS compliance, evaluate potential safety recalls, draft and review documents for NHTSA, participate in cross-functional safety and product development meetings, and perform targeted legal research to support regulatory submissions and Ford's compliance with NHTSA orders.

Drive procurement of indirect software and services through data analysis, sourcing (RFI/RFP/RFQ), contract negotiation (SOWs/SLAs), supplier relationship management, onboarding due diligence, and category roadmap development to deliver cost savings and mitigate risk.

Own integrated execution across the data-to-reporting value stream: maintain unified schedules, dependencies, risks and readiness; drive Jira and Agile delivery hygiene; facilitate cross-team collaboration from requirements through UAT; manage critical path, release planning, and leadership reporting to ensure data/reporting launch readiness.