HYBRID / 4 DAYS PER WEEK IN OFFICE ORDER IS BILLING TO A PD DEPARTMENT THAT REQUIRES THE FORD PEOPLE LEADER TO OBTAIN A SECOND APPROVAL TO EXTEND AN OFFER Please direct all questions or concerns regarding this order to Susan Davis and Kathleen Sheedlo via email. As this is a hybrid position, the customer may request in-person interviews. Agency employees are required to be onsite from day one, as specified. Please do not submit remote-only candidates. If a candidate plans to relocate, note in the submittal that the relocation will be at the candidates own expense. 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 tomorrows transportation. Modern vehicles are increasingly software-defined, connected, and intelligent. Delivering a best-in-class ownership and service experience now depends on Fords 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? Fords 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. As a Systems Engineer End to End Software Diagnostics &
- Observability, you will work with a cross-functional team responsible for defining, integrating, and maturing intelligent diagnostic workflows that span embedded vehicle behavior, cloud-based observability, AI reasoning engines, and human support processes. This role is ideal for a highly capable recent graduate or early-career engineer from a top engineering, computer science, or AI/ML program who wants to work on real-world AI systems for software-defined vehicles.

Competency Group: All Information Systems

Security Check Reqd: Y

Estimated Regular Hours: 0

Estimated Overtime Hours: 0

Standard Shift: Morning

Travel Required? N

Travel %: 0

Division

Skills Required

Systems Development Life Cycle, Software Systems, Systems Engineering, Product Management, Systems Architecture, Systems Analyst 1.

Software Systems

Understand how an applications components work together, and help troubleshoot issues across the system. 2.

Systems Analyst

Gather and document user or business requirements, analyze current processes,



and translate needs into functional specifications. 3.

Systems Architecture

Understand or help document how systems and components fit together, including integrations, data flows, and technology choices. 4.

Systems Development Life Cycle

Participate in the stages of system delivery, from requirements and design through development, testing, deployment, and maintenance. 5.

Systems Engineering

Help define system requirements and ensure components work together to meet performance, reliability, and operational needs. 6.

Product

Management - Help prioritize features, maintain a product backlog or roadmap, and coordinate with stakeholders and development teams.

Skills Preferred

Python, GCP, Java, Artificial Intelligence &

- Expert Systems 1.

Artificial

Intelligence &

- Expert Systems Understand or contribute to a basic AI or rules-based feature, such as classifying requests or recommending a next step, while recognizing when human review is needed.
- GCP Use Google Cloud services to deploy or support an application, store data, or monitor a cloud-based system. 3.

Python

Write or maintain basic Python scripts for automation, data processing, or application functionality.

- Java - Write or maintain Java code for application features, business logic, and error handling.

Experience Required

Bachelors or Masters degree in Computer Science, Computer Engineering, Electrical Engineering, Systems Engineering, Artificial Intelligence, Machine Learning, Robotics, Data Science, or related field. 3-6 years of experience in AI/ML engineering, embedded software, systems engineering, cloud engineering, or related areas through internships, research, academic projects, or full-time work. Solid academic foundation in AI/ML engineering with practical familiarity in machine learning, LLMs, retrieval workflows, inference systems, model evaluation, and data pipelines. Strong proficiency in Python.

Familiarity with AI/ML prototyping and engineering workflows, including training, inference, prompt-based systems, retrieval-augmented workflows, embeddings, ranking, or reasoning pipelines. Familiarity with software engineering fundamentals, APIs, Git-based development, and containerized application workflows. Interest in embedded systems, vehicle diagnostics, software-defined vehicles, and intelligent support workflows.

Ability to translate ambiguous problem statements into structured technical requirements and system behavior. Strong written and verbal communication skills and requirements authoring with the ability to drive high level abstract conversations with leadership. Demonstrated ability through coursework, research, internships, or projects to build or prototype AI/ML enabled systems.

Experience Preferred

Education from a highly regarded engineering, computer science, or AI/ML program with strong evidence of technical rigor. Hands-on experience with LLMs, semantic retrieval, vector search,



ranking systems, agent-based workflows, or decision-support systems.

Experience with PyTorch, TensorFlow, scikit-learn, LangChain, Vertex AI, BigQuery, or similar AI/ML and cloud tools.

Experience building chatbots, copilots, AI assistants, search systems, or reasoning systems. Familiarity with evaluation of AI systems for grounding, confidence, traceability, explainability, and policy compliance. Familiarity with embedded software systems, electronic control modules, diagnostics, or connected vehicle technologies.

Exposure to DTCs, PIDs, Freeze Frame data, logs, vehicle network data, or diagnostic workflows. Familiarity with GCP, Docker, GitHub, CI/CD, and observability tools such as Dynatrace or Grafana.

Experience through internships, research, or projects involving distributed systems, platform integration, or cloud-native services. Ability to work well in a collaborative, agile environment with software, embedded, cloud, AI, and product teams. Strong curiosity, ownership mindset, and willingness to learn quickly in a technically demanding domain. Ability to be detail oriented while understanding broader system and product goals.

Education Required

Bachelor's Degree

Education Preferred

Master's Degree

Original Duration: 364 Days

Additional Information

Help define system-level requirements, interfaces, and workflows for Fords End to End Software Diagnostics &

- Observability initiative. Support development of AI-powered embedded vehicle diagnostics capabilities that improve issue detection, case intake quality, root-cause isolation, and guided repair. Work across embedded, cloud, data, and AI/ML domains to connect vehicle diagnostics with intelligent reasoning and observability workflows. Help translate business, service, and engineering needs into technical requirements for diagnostic systems, AI engines, APIs, workflow orchestration, and support tooling. Support AI/ML driven capabilities such as case intake assistance, knowledge retrieval, diagnostic reasoning, decision support, validation, and orchestration. Define and refine requirements for diagnostic evidence collection, including DTCs, PIDs, Freeze Frame data, logs, event traces, module state, and procedural outcomes. Support design of systems that combine Ford engineering knowledge, diagnostics data, and AI reasoning to isolate likely root causes in embedded vehicle systems. Participate in evaluation and validation of AI system behavior using diagnostic evidence, service data, engineering content, and observability signals. Work with internal teams and suppliers to integrate containerized AI solutions into Ford-managed cloud environments and workflow systems. Help define observability requirements for diagnostic systems, including logs, metrics, traces, dashboards, alerts, and escalation workflows. Participate in system integration, issue triage, root-cause analysis, and cross-functional technical problem solving. Support rapid iteration, testing, and deployment of AI-enabled diagnostic capabilities into engineering and non-production environments. Communicate technical tradeoffs, risks, and recommendations clearly to engineering teams, product teams, and leadership. Work under the guidance of experienced engineers.

📌 Technical Program & Project Management Senior Associate (Kanata)
🏢 KYYBA
📍 Kanata