Director, Core Runtime & Platform Engineering

Ford Ford · Auto · Palo Alto, CA +1 · Manufacturing

Director of Core Runtime & Platform Engineering at Ford, leading the development of the foundational platform stack for software-defined manufacturing. This includes the operating and orchestration layer (CoreOS), the real-time signal and decisioning layer (FMIL), and the data platform (CoreDS). The role focuses on architecting and delivering the runtime, edge, connectivity, cloud infrastructure, developer platform, and reliability layers that enable these systems to operate securely and at scale across global manufacturing environments. Responsibilities include building the platform backbone, developer APIs/SDKs, industrial edge computing, device connectivity, hybrid cloud infrastructure, real-time data pipelines, observability, and ensuring reliability and global scale.

What you'd actually do

  1. Lead the Core Runtime Platform
  2. Build the Core Developer Platform (APIs & SDKs)
  3. Industrial Edge & Distributed Systems
  4. Device Connectivity & Industrial Middleware
  5. Cloud & Hybrid Platform Infrastructure

Skills

Required

  • Software engineering leadership
  • Platform architecture
  • Runtime systems
  • Edge computing
  • Distributed systems
  • Cloud infrastructure (AWS, GCP, Azure)
  • Kubernetes
  • Developer platforms (APIs, SDKs)
  • Industrial automation/middleware
  • Real-time data processing
  • Observability tools (Prometheus, Grafana, OpenTelemetry)
  • Reliability engineering (SRE)
  • Security best practices

Nice to have

  • Experience in manufacturing environments
  • Knowledge of industrial protocols (EtherCAT, Profinet, OPC UA, MQTT, etc.)
  • Experience with AI/ML data pipelines

What the JD emphasized

  • secure, scalable execution layer
  • real-time signal, orchestration, and decisioning layer
  • edge computing platforms for real-time manufacturing environments
  • high-throughput, low-latency workloads
  • resilient edge runtimes
  • middleware connecting PLCs, robotics, vision systems, and industrial equipment
  • high-fidelity data pipelines supporting AI/ML, diagnostics, analytics, and traceability
  • platform-wide observability across edge and cloud environments
  • mission-critical manufacturing systems