Systems Engineer – End-to-End Software Diagnostics & Observability
About The Position
Modern vehicles are increasingly software-defined, connected, and intelligent. Delivering a best-in-class ownership and service experience now depends on Ford’s ability to detect, understand, diagnose, and resolve complex software and electronics issues quickly and accurately. Ford is investing in an End-to-End Software Diagnostics & Observability initiative focused on transforming how vehicle issues are understood across engineering, diagnostics, and service workflows. We are building state-of-the-art AI-powered Embedded Vehicle Diagnostics capabilities that combine vehicle signals, diagnostics, logs, engineering knowledge, service procedures, and intelligent reasoning to improve case quality, accelerate fault isolation, guide next-best actions, and support scalable human-in-the-loop escalation. This initiative sits at the intersection of embedded systems, cloud services, diagnostics, observability, and AI/ML engineering. The team is a fast-paced, highly collaborative organization that translates advanced technical strategy into deployable capabilities. As a Systems Engineer – End-to-End Software Diagnostics & Observability within the Electric Vehicles, Digital and Design (EVDD) team, you will not be a "siloed" contributor. You will sit at the epicenter of Embedded Systems, Cloud Architecture, and AI/ML Engineering, owning the entire birth-to-deployment journey of intelligent diagnostic workflows. You will be the architect of the data’s journey—from the vehicle's silicon to the cloud’s neural networks—ensuring that our systems are production-hardened, scalable, and serve a diverse global ecosystem of remote users, 3rd-party technicians, and enterprise stakeholders.
Requirements
- Embedded Systems
- Cloud Architecture
- AI/ML Engineering
- Understanding of vehicle signals, diagnostics, and logs
- Knowledge of engineering knowledge and service procedures
- Experience with intelligent reasoning
- Ability to work in a fast-paced, highly collaborative organization
- Passion for AI/ML, complex systems, embedded software, and solving real-world engineering problems at scale
Responsibilities
- Owning the entire birth-to-deployment journey of intelligent diagnostic workflows.
- Architecting the data's journey from the vehicle's silicon to the cloud's neural networks.
- Ensuring systems are production-hardened, scalable, and serve a diverse global ecosystem of remote users, 3rd-party technicians, and enterprise stakeholders.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
