Systems Engineer

Ford Ford · Auto · Dearborn, MI +1 · PD Operations and Quality

Systems Engineer role focused on building AI-powered embedded vehicle diagnostics and observability platforms. The role involves full-lifecycle ownership from embedded systems to cloud AI/ML engineering, integrating vehicle signals, logs, and diagnostic data to automate root-cause analysis and guide repair actions. It bridges embedded C++ and cloud Python, defines telemetry requirements, and validates AI reasoning for diagnostic workflows.

What you'd actually do

  1. You will partner with cross-functional teams to define "what" a vehicle needs to observe. You will write the technical requirements that govern how ECUs log data and how the Cloud interprets it.
  2. You will bridge the gap between Embedded C++ firmware and Cloud-based Python microservices. You will ensure that the "handshake" between the vehicle and the AI reasoning engine is seamless and scalable.
  3. You will help mature the intelligent diagnostic workflows, ensuring the AI has the right "context" (DTCs, PIDs, and logs) to perform automated root-cause analysis.
  4. You will lead the system integration testing, simulating complex failures to ensure our E2E pipeline triggers the correct alerts and human-support processes.
  5. You will analyze real-world telemetry to refine requirements and iterate on the next generation of diagnostic capabilities.

Skills

Required

  • BS equivalent or higher degree in Computer Science, Systems Engineering, Electrical Engineering, or a related technical field
  • Minimum 3.5 cumulative GPA

Nice to have

  • Embedded C++
  • Cloud-based Python microservices
  • AI/ML engineering
  • diagnostics
  • observability
  • telemetry
  • data lakes
  • AI reasoning engines
  • vehicle signals
  • logs
  • service procedures
  • fault isolation
  • next-best actions
  • human-in-the-loop escalation
  • software-defined vehicles
  • connected vehicles
  • intelligent vehicles
  • ECUs
  • DTCs
  • PIDs
  • API contracts
  • embedded gateway
  • cloud-based diagnostic orchestrator
  • ground truth data

What the JD emphasized

  • AI-powered Embedded Vehicle Diagnostics
  • End-to-End Software Diagnostics & Observability platform
  • Embedded Systems, Cloud Architecture, and AI/ML Engineering
  • Embedded C++ firmware and Cloud-based Python microservices
  • AI reasoning engine
  • automated root-cause analysis
  • AI diagnostic models
  • AI systems interpret diagnostic evidence
  • AI agent

Other signals

  • AI-powered diagnostics
  • intelligent reasoning engines
  • embedded systems
  • cloud services
  • diagnostics
  • observability
  • AI/ML engineering