Hybrid Staff Engineer

at Ford Motor Company

• Job title: Staff Engineer
• Job type: Full Time
• Experience level: Lead
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: BigQuery, Cloud, Distributed Systems, Google Cloud Platform, Kafka, NoSQL, SDLC
• Location requirements: Hybrid, Chennai, India

About the role

• Lead architectural overhaul of Ford's Connected Vehicle Data Platform, focusing on AI-driven data architecture and streaming systems.

Responsibilities

• 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.

Requirements

• 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.

Benefits

• Join Us in Re-driving the Future of Automotive Data at Ford!