Currently tracking 13 active AI roles, down 11% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $85k–$233k (avg $147k).
Ford has 20 active job listings related to artificial intelligence. The majority of these roles, 60%, are focused on agents. Engineering is the dominant function, with 17 positions, and hiring is concentrated in the United States. Frequent technology tags include agent orchestration, RAG, and LLM observability, suggesting a focus on building and deploying AI agents. In the last 30 days, Ford has added 21 new AI roles, representing a 600% increase from the previous 30-day period.
Ford currently has 33 active AI-related roles in our index. The most common open titles are: AI Engineer (2), Data Scientist (2), Analytics Integration Specialist, Applied AI/ML Software Engineer-Supply Chain AI and Decision Intelligence, Chief Engineer, AI Product Creation. Most positions are in Engineering and Product.
Ford's active AI hiring is concentrated in: agents (64%), application (15%), serving infrastructure (9%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Ford is hiring AI talent in: United States (33 roles).
Job postings at Ford most frequently reference: agent orchestration, model serving, rag, llm observability, inference infra.
In the past 30 days, Ford has posted 33 new AI-related roles. That is a +57% change versus the prior 30 days (21 → 33).
| Title | Stage | AI score |
|---|---|---|
| Manager, Uptime AI Product Manager for Uptime AI at Ford, focused on transforming the Customer Service Division's ecosystem into a proactive, AI-driven pipeline. The role centers on the Quality Early Warning (QEW) system, utilizing LLMs and advanced analytics to detect vehicle concerns early, reduce repair order duration, and prevent SLA breaches. Responsibilities include collaborating with data scientists, leading proactive system innovation, developing strategic action plans, and owning dashboards and executive storytelling. | Agent | 7 |
| Product Manager & Data Science Supervisor This role supervises a global cross-functional team of data scientists, analysts, engineers, and designers to deliver analytics-driven solutions and product initiatives. The responsibilities include identifying opportunities for process optimization via data-driven approaches, organizing large datasets, applying data mining and machine learning models, creating visualizations, and working with IT to implement analytics tools. The role involves developing analytic models, supporting Reductive Design decisions, formulating problems, translating business requirements into analytical projects, and communicating findings to various stakeholders. It also includes project ownership, planning, tracking, and building advanced analytics models in the supply chain space, with a specific requirement for developing, fine-tuning, and deploying LLMs for NLP tasks. |
| AgentData |
| 7 |