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AI Data Foundation Engineer at Ford Motor Company
, , India -
Full Time

Start Date

Immediate

Expiry Date

13 Oct, 26

Salary

0.0

Posted On

15 Jul, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Python, SQL, Spark, Beam, Dataflow, Cypher, Gremlin, Airflow, Dagster, Cloud Composer, GCP, BigQuery, Knowledge Graphs, RAG, Vector Stores, CI/CD

Industry

Motor Vehicle Manufacturing

Description
As an AI Data Foundation Engineer in the Supply Chain AI and Decision Intelligence space, you will be the driving force for delivering Ford's "AI-First" supply chain transformation. This role is focused on engineering the intelligent data backbone , the pipelines, knowledge graphs, and AI-ready data platforms  that fuel high-performance models (internal or external, e.g., from COTS products) and continuously enrich Enterprise Knowledge Graphs to solve complex supply chain problems. Central to this role is the adoption of an AI-Native Data Engineering SDLC, leveraging agentic workflows, AI-assisted coding, and automated testing to deliver robust, high-quality, model-ready data at industrial speed. You will bridge the gap between raw, fragmented enterprise data and the trusted, governed, AI-ready data foundation that powers supply chain AI/ML systems, decision-intelligence engines, and Generative AI applications. This role demands a blend of technical expertise in data engineering, AI/ML data enablement, and platform architecture, functional expertise in supply chain, and strong technical leadership to influence stakeholders and deliver transformative results with a particular focus on establishing and standardizing the AI-centric data engineering SDLC and data quality frameworks across cross-functional teams. You aren't just moving data ,you are engineering the intelligence layer beneath a global supply chain, building the foundation of trust and reliability that allows AI to manage risk, build resilience, and keep factories running.
Responsibilities
Engineer the intelligent data backbone, pipelines, and knowledge graphs to support AI-first supply chain transformation. Establish an AI-native data engineering SDLC to deliver high-quality, model-ready data for Generative AI and decision-intelligence engines.