Systems Engineer - End-to-End Software Diagnostics & Observability

At Ford Motor Company, we believe freedom of movement drives human progress. With our exciting plans for the future of mobility, we have a wide variety of opportunities for you to accelerate your career potential as you help us define tomorrow's transportation. Why Join EVDD? You'll join an agile team of doers pioneering our EV future. We are customer-obsessed, entrepreneurial, and data-driven. 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. That is why 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. Do you want to help define the future of AI-enabled diagnostics for next-generation vehicles? Ford's team is a fast-paced, highly collaborative organization that translates advanced technical strategy into deployable capabilities. If you are passionate about AI/ML, complex systems, embedded software, and solving real-world engineering problems at scale, consider joining our forward-thinking team.

The Mission:

Building the Nervous System of the SDV At Ford Motor Company, we believe freedom of movement drives human progress. As vehicles become software-defined, intelligent, and connected, our ability to compete depends on a fundamental shift: moving from reactive diagnostics to proactive observability . We are overhauling our global legacy systems to build a state-of-the-art End-to-End (E2E) Software Diagnostics & Observability platform . This is the "nervous system" for our next generation of vehicles-an intelligent pipeline that integrates embedded telemetry, cloud-based data lakes, and AI reasoning engines to resolve complex issues before they impact the customer.

The Role:

Full-Lifecycle Ownership 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.

Core Responsibilities Cradle-to-Grave Feature Ownership:

Partner with cross-functional teams to define "what" a vehicle needs to observe, write the technical requirements (ECU logging/Cloud interpretation), and lead the integration through to global production monitoring.

The Quality Gatekeeper:

Define and enforce the "Definition of Done" for diagnostic workflows. You are essential to ensuring that code is not only functional but observable, maintainable, and meets Ford's rigorous production benchmarks. Engineering for

Personas:

Tailor system behavior and data visualization for a diverse user base. Ensure a 3rd-party technician gets a "repair hint," a remote driver experiences a seamless fix, and an enterprise engineer receives high-fidelity raw telemetry.

Technical-to-Business Translation:

Distill complex system telemetry into actionable insights. You must be able to communicate technical tradeoffs and root-cause analyses clearly to both deep-tech engineering teams and non-technical leadership.

The Intelligence Loop:

Engineer AI-powered diagnostic capabilities that combine vehicle signals (DTCs, PIDs, Ethernet logs) with LLM-based reasoning (RAG) to automate root-cause isolation.

Production Validation:

Lead system integration testing and simulate complex failure modes (FMEA) to ensure our E2E pipeline triggers the correct alerts and human-in-the-loop support processes.

Minimum Qualifications Academic Foundation:

BS or equivalent or higher degree in Computer Science, Systems Engineering, Electrical Engineering, or a related technical field . Minimum 3.5 cumulative GPA (or equivalent evidence of technical rigor).

Python & Automation Mastery:

1+ years of experience writing 2,000+ lines of clean, PEP8 compliant, modular Python code for data processing, API integration, or system automation.

Production System Integration:

1+ years of experience with Git-based version control (minimum 50+ commits/merges) and containerization (Docker) , including deploying at least 3 containerized applications to a cloud or local environment.

AI/ML Implementation:

1+ years of professional/research experience in at least 2 end-to-end AI/ML projects involving LLM orchestration (e.g., LangChain) or deploying a reasoning agent into a "live" state.

Data Integrity:

1+ years of experience processing and cleaning datasets exceeding 10,000+ records for model training or inference.

Technical Documentation:

1+ years of experience translating ambiguity into structure by authoring at least 3-5 detailed technical specifications (e.g., API contracts, System Requirements, or Sequence Diagrams).

Problem Solving:

1+ years of experience debugging complex systems (Embedded or Cloud), resolving at least 5-10 high-priority technical blockers using Root Cause Analysis (RCA).

Even Better If You Have Production Track Record:

Experience leading at least 1 significant software module through the full lifecycle from initial requirements to a live, production environment with active users.

Embedded Protocols:

1+ years of experience using logic analyzers or tools (Wireshark/CANoe) to decode 3+ automotive protocols (e.g., CAN, DoIP, or SOME/IP).

Cloud Observability:

Experience building real-time production dashboards in Grafana, Dynatrace, or Datadog to monitor system health and "drift."

Systems Engineering Rigor:

Experience authoring 5+ pieces of critical production documentation (FMEA, Interface Control Documents, or Production Validation Plans).

Scale:

Experience working on a system that handled 1,000+ concurrent nodes or data streams , demonstrating an understanding of horizontal scalability. You may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply! As an established global company, we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe, or keep you close to home? Will your career be a deep dive into what you love, or a series of new teams and new skills? Will you be a leader, a changemaker, a technical expert, a culture builder...or all of the above? No matter what you choose, we offer a work life that works for you, including: Immediate medical, dental, vision and prescription drug coverage Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care and more Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more Vehicle discount program for employees and family members and ma