Ford
Auto · Automaker
- HQ
- Dearborn, US
- Founded
- 1903
- Size
- 180,000+
- Website
- ford.com
Ford currently has 28 active AI-related job listings. The majority of these roles, 50%, are focused on agents, with application roles making up another 21%. Engineering is the most frequent function hiring for these positions. Recent hiring trends show a decrease, with 23 new AI roles posted in the last 30 days, a 42% reduction compared to the preceding 30-day period.
Ford currently has 28 active AI-related roles in our index. The most common open titles are: Full Stack Software Engineer - AI Applications (2), AI Platform Administrator, Autonomous Robotics Launch Manager, Chief Engineer, AI Product Creation, DAT In-House Perception Algorithm Engineer. Most positions are in Engineering and Product.
Ford's active AI hiring is concentrated in: agents (57%), application (18%), serving infrastructure (14%). 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 (28 roles).
Job postings at Ford most frequently mention: Statistics, Python, Predictive Modeling, Machine Learning, GCP.
In the past 30 days, Ford has posted 22 new AI-related roles. That is a -41% change versus the prior 30 days (37 → 22).
Currently tracking 18 active AI roles, with 460 new openings in the last 4 weeks. Primary focus: Agent · Engineering. Salary range $65k–$268k (avg $158k).
| Title | Stage | AI score |
|---|---|---|
| Senior Software Engineer Senior Software Engineer role focused on building and deploying Generative AI, LLM-powered applications, RAG pipelines, and multi-agent systems within an industrial analytics context on Google Cloud Platform (GCP). The role involves full-stack development, cloud infrastructure management with Terraform, and leveraging AI tools for software engineering. | Agent | 7 |
| AI Platform Administrator The AI Platform Administrator is responsible for the operational governance, security, lifecycle management, and enterprise adoption of AI agents and agentic capabilities across the organization. This role serves as a platform lead helping to define strategy for agentic AI solutions across Microsoft Copilot, Google Gemini, Anthropic, and use of LLMs within the enterprise. The position ensures AI solutions are deployed securely, comply with corporate governance requirements, align with enterprise architecture standards, and deliver measurable business value. The AI Administrator works closely with developers, architects, cybersecurity, compliance teams, platform engineers, and business stakeholders to establish a scalable and governed AI ecosystem. | Agent | 7 |
| Autonomous Robotics Launch Manager Lead a multi-plant engineering team to define, develop, and deploy next-generation autonomous robotics technologies for Ford's manufacturing logistics. This role oversees AMR/AGV platforms, embedded controls, ML-based perception, ADAS-inspired autonomy, and large-scale software integrations. Responsibilities include technical leadership for autonomy software, sensor fusion, perception, mapping, localization, motion planning, and safety systems, as well as software-driven project execution and multi-plant launch leadership. The role also involves embedded controls and hardware integration, and software validation using simulation environments. | AgentData | 7 |
| Full Stack Software Engineer - AI Applications Full Stack Software Engineer focused on building and orchestrating AI agents and applications within an enterprise context, emphasizing cloud-native development on GCP and integrating various systems. The role involves designing, deploying, and operating AI-powered applications, RAG pipelines, and LLM integrations, with a focus on developer productivity and automation. | Agent | 7 |
| Director, AI Transformation Architect Director-level role focused on identifying, redesigning, and scaling AI-enabled workflows within Ford's Integrated Services organization. The role involves hands-on building and prototyping of AI agents, automation, and infrastructure to improve speed, quality, and decision-making across product management, engineering, and go-to-market functions. It emphasizes responsible AI implementation, governance, and driving adoption through training and best practices. | Agent | 7 |
| Senior Software Engineer — DevOps & Platform, AI Systems Senior Software Engineer focused on building and operating the cloud-native AI platform at Ford, emphasizing automation, agent orchestration for operational tasks, and supporting AI workloads like LLMs and agentic systems. The role involves designing and managing GCP infrastructure, CI/CD pipelines, and ensuring reliability and security for AI systems. | AgentServe | 7 |
| Full Stack Software Engineer - AI Applications This role focuses on building and shipping AI-powered applications and agents, specifically RAG pipelines, LLM integrations, and agentic workflows, within an enterprise context. The engineer will orchestrate agents for development, connect disparate systems, and automate manual processes, while also owning the cloud-native infrastructure on GCP and CI/CD pipelines. The emphasis is on practical application and production deployment of AI within a large organization. | Agent | 7 |
| Sr. Manager, Yield Management - GTM Advanced Analytics Senior Manager to lead the strategic development, deployment, and enhancement of AI/ML solutions for Yield Management at Ford. This role involves leading a team to transform business processes using predictive modeling, forecasting, segmentation, and optimization algorithms, with a focus on delivering end-to-end production-grade AI solutions. Key responsibilities include managing the AI/ML lifecycle, developing demand sensing algorithms, driving innovation with Agentic AI, establishing MLOps and Responsible AI practices, and collaborating with business stakeholders. | AgentData | 7 |
| DAT In-House Perception Algorithm Engineer Develops and integrates ADAS perception algorithms using C++ for embedded systems, applying machine learning and computer vision techniques to ADAS solutions with sensors like LiDAR, Radar, USS, and Camera. Requires experience in ADAS vehicle testing, data processing, validation, MISRA C++ coding standards, CI/CD pipelines, Git, and Agile methodologies. | Agent | 7 |
| Software Engineer, AI Enablement Software Engineer to design and build AI-powered agents for intelligent discovery, recommendation, and management of enterprise ontology assets, requiring strong software engineering skills and practical AI experience in information discovery, recommendation, and search. | Agent | 7 |
| Principal AI/ML Engineer (Cybersecurity & AIOps) Principal AI/ML Engineer focused on cybersecurity and AIOps, leading the design, development, and deployment of AI/ML solutions. This role involves building and operationalizing models for anomaly detection, predictive analytics, and classification, with a strong emphasis on Generative AI and Agentic AI for automation and threat intelligence. The engineer will architect ML pipelines, work hands-on with data, and translate technical outcomes for stakeholders, bridging data science with security operations. | AgentServe | 7 |