Principal Engineer - AI-Driven Connected Vehicle Data Platform

Principal engineer

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. 

• AI-Driven Data Architecture: Lead the design and evolution of a data architecture that natively integrates AI/ML. Architect systems where data is "AI-ready" from ingestion, ensuring seamless compatibility with Large Language Models (LLMs) and predictive analytics. 

• Agentic Flows & AI Agents: Design and develop autonomous Agentic flows and AI agents tasked with intelligent data collection, automated metadata tagging, and real-time anomaly detection. Build frameworks where agents can generate proactive insights from vehicle telemetry to identify issues before they lead to recalls or warranty claims. 

• Technical Leadership & Mentorship: Act as the primary technical lead for a cross-functional group of software and data engineers. Provide deep technical mentorship in both traditional data engineering and modern applied AI/ML practices. 

• Architectural Strategy: Define the long-term roadmap for the platform, ensuring it can handle high-throughput, low-latency streaming data from millions of vehicles while supporting complex AI-driven workloads. 

• Data Product Innovation: Lead the transition from raw data pipelines to "Intelligent Data Products," ensuring vehicle data is high-quality, democratized, and enriched by AI for global compliance and business use cases. 

• Hands-on Engineering: Lead by example by contributing to critical codebase components, prototyping Agentic frameworks, and solving the most complex technical bottlenecks in our AI and data pipelines. 

• Platform Scalability & Reliability: Oversee the design of highly available, fault-tolerant pipelines that scale elastically to eliminate data fragmentation across the Ford enterprise. 

• Engineering Standards: Establish best practices for MLOps and LLMOps, ensuring that AI models and agents are deployed, monitored, and versioned with the same rigor as production code. 

• Compliance & Global Standards: Partner with security and compliance teams to ensure AI-driven data use cases meet evolving global regulations and protect customer privacy. 

• Education: Minimum – Bachelor’s Degree in Computer Science, Information Technology, or a related field. Preferred – Master’s Degree in a highly technical field (Computer Science, Mathematics, or Physics) with a focus on AI/ML. 

• Experience: 15+ years of experience in software and data engineering, with at least 5 years focused on large-scale connected vehicle or IoT streaming platforms. 

• AI/ML Expertise: Proven experience in Applied AI, including the development of Agentic workflows (e.g., using frameworks like LangChain, CrewAI, or AutoGPT) and the integration of LLMs into enterprise data pipelines. 

• Data Architecture: Deep understanding of modern data architectural patterns (Data Lakehouse, Mesh) and how to optimize them for AI/ML consumption. 

• Technical Authority: Previous experience as a Principal or Staff-level engineer leading the architecture of enterprise-scale distributed systems. 

• Cloud & AI Stack: Expert-level experience with Google Cloud Platform (GCP), specifically BigQuery, Dataflow, and Vertex AI. Experience with Vector Databases (e.g., Pinecone, Weaviate) and RAG (Retrieval-Augmented Generation) architectures. 

• Streaming & Messaging: Deep expertise in streaming technologies (Kafka, Pub/Sub) and managing high-throughput topics for real-time AI inference. 

• DevOps & MLOps: Expert knowledge of SDLC, CI/CD, and MLOps frameworks to manage the lifecycle of AI agents and data models. 

• Optimization: Ability to optimize compute costs for both high-scale data processing and AI/ML inference in cloud environments. 
  
  

• Why Join Ford? 

• • Be the technical architect of Ford’s AI transformation, directly influencing the 2026 MY+ vehicle lineup. 

• • Work at the intersection of massive-scale IoT data and cutting-edge Agentic AI. 

• • Solve "hard" engineering problems in a culture that values technical depth and innovation. 

• • Competitive compensation, benefits, and the opportunity to lead the next generation of automotive intelligence. 

• Join Us in Architecting the AI-Driven Future of Data at Ford! 

Experience Level

Senior Level