About Connected Vehicle Data Platform:
At Ford, data is at the heart of our transformation towards becoming a technology-driven mobility company. Connected Vehicle Data Platform's mission is to build foundational, company-wide systems and processes designed to intelligently collect, manage, control, and democratize all vehicle-related data as key data products. Its purpose is to eliminate data fragmentation and duplication, enabling robust cloud and vehicle data capabilities that facilitate proactive issue identification, reduce regulatory penalties, recalls, and warranty claims, and ensure global compliance for evolving data use cases, especially for 2026 MY+ vehicles.
Summary:
We are seeking a visionary Principal Engineer to serve as the technical authority for our Connected Vehicle Data Platform(200+ engineering org), with a specific focus on AI-driven data architecture. In this role, you will bridge the gap between Software Engineering, Data Engineering, and Applied AI. You will drive the architectural vision for how we process massive streams of vehicle data and lead the implementation of Agentic flows and AI agents to automate data collection, governance, and insight generation.
The ideal candidate is a "player-coach" who remains hands-on in the code while providing high-level technical leadership. You will be responsible for designing resilient streaming architectures that leverage the latest in AI/ML to ensure our 2026 MY+ vehicle data is not just stored, but intelligently utilized to drive proactive business decisions.
Grounds-Up Streaming Re-architecture: Lead the technical vision and execution for re-building the connected vehicle streaming foundation. Replace legacy systems with a modern, high-throughput, and low-latency stack designed for global scale and efficiency.
IC Leadership of Senior Talent: Act as the primary technical mentor and lead for the portfolio’s Staff and Senior Staff Engineers. Drive technical alignment across an 80+ person engineering organization through RFCs, architecture reviews, and "Golden Path" implementations.
Advanced Data Modeling: Define the standards for database and time-series data modeling. Architect specialized schemas for high-cardinality vehicle telemetry that balance high-speed ingestion with cost-effective, performant querying.
Agentic Data Insights: Design and develop AI Agentic flows that revolutionize how Ford interacts with data. Move beyond static dashboards by building agents capable of autonomously "answering data questions" interpreting natural language queries to generate real-time insights from billions of vehicle data points.
AI-Driven Efficiency: Architect systems where Applied AI/ML is used to drive massive efficiency gains. This includes intelligent data pruning, automated anomaly detection, and AI-optimized compute resource allocation (GCP Dataflow/Dataproc).
Agentic Data Collection: Develop autonomous agents for "Intelligent Ingestion," enabling self-healing pipelines and automated metadata tagging to eliminate data fragmentation and ensure global compliance.
Efficiency & Cost Ownership: Lead the technical strategy for optimizing cloud unit economics. Drive architectural changes that significantly reduce the total cost of ownership (TCO) for vehicle data products while increasing reliability.
Hands-on Excellence: Maintain a high level of technical craft by prototyping the most difficult segments of the architecture and solving the portfolio’s most complex technical bottlenecks.
Education: Minimum – Bachelor’s Degree in Computer Science, Data Engineering, or a related field. Preferred – Master’s or PhD in a highly technical field.
Experience: 10+ years of professional experience in software and data engineering, with a proven track record of architecting large-scale (Petabyte-scale) streaming and distributed systems.
IC Leadership: Demonstrated experience as a Staff or Senior Staff Engineer (or equivalent) providing technical leadership for large organizations (50-100+ engineers).
Modeling Expertise: Expert-level knowledge of Database Modeling (Relational, NoSQL) and specialized Time-Series Data Modeling (e.g., handling high-frequency sensor data, windowing, and compaction).
AI & Agentic Mastery: Deep hands-on experience in Applied AI, including the development of Agentic workflows (e.g., LangChain, CrewAI) and utilizing LLMs to automate data exploration and insight generation.
Streaming & Cloud Stack: Expert proficiency in Google Cloud Platform (GCP), specifically BigQuery, Dataflow, and Vertex AI. Mastery of Kafka or Pub/Sub for high-throughput messaging.
Efficiency Mindset: Proven ability to re-drive architectures specifically for efficiency gains, cost reduction, and performance optimization in a cloud-native environment.
Modern Engineering Standards: Mastery of SDLC, MLOps, and LLMOps, with the ability to set the standard for testing, observability, and deployment of AI-integrated data systems.
Technical Sovereignty: As the lead IC for the portfolio, you have the autonomy to re-drive the foundation of Ford’s connected vehicle future.
Scale & Complexity: Work with one of the world's largest and most complex IoT datasets.
Innovation: Lead the industry move from "Data Pipelines" to "Agentic Data Ecosystems."
Impact: Directly influence the safety, compliance, and efficiency of the 2026 MY+ vehicle fleet.
Join Us in Re-driving the Future of Automotive Data at Ford!
