Ford

Seeking an experienced Data Scientist to architect, develop, and deploy end-to-end agentic Generative AI full-stack applications for engineering challenges. This role involves designing MLOps pipelines, integrating cloud AI tools, developing front-end interfaces, and translating business needs into AI/ML solutions.

Full Stack Software Engineer focused on integrating AI, specifically LLMs, into applications. The role involves architecting systems with autonomous agents, utilizing a Model Context Protocol for live data interaction, and providing real-time streaming experiences. Key responsibilities include designing agentic loops, implementing tool-use capabilities, integrating with proprietary data silos, developing high-concurrency back-ends and streaming front-ends, optimizing RAG pipelines, and establishing AI evaluation and observability.

Applied AI/ML Engineer to lead Ford's AI-First supply chain transformation by integrating AI models into Enterprise Knowledge Graphs. The role focuses on applied implementation, agentic workflows, and an AI-Driven SDLC to solve complex supply chain problems, manage risk, and build resilience. Responsibilities include business requirement gathering, model integration, graph-based AI implementation, AI-Driven SDLC execution, pipeline/MLOps engineering, and technical standardization.

Data Engineer role focused on building and scaling end-to-end data and AI pipelines on GCP, integrating Gen AI capabilities like LLM-powered enrichment, RAG, and intelligent automation. Responsibilities include designing data models, implementing CI/CD, data governance, and mentoring junior talent, with a focus on powering AI/ML workloads and next-generation AI experiences.

This role focuses on developing and automating backend pipelines for platform systems engineering at Ford, including requirements, DFMEA, and capability dictionaries. It involves automating gap analysis, optimizing engineering processes, and using LLMs for quality analysis of engineering artifacts. The role also involves leading DevOps process design, experimenting with automation for pipeline processes, and integrating cross-functional team inputs.

Staff Platform Software Engineer at Ford focused on building intelligent systems and agentic capabilities within the Enterprise Data Platform. The role involves defining best practices, leading architectural design, optimizing petabyte-scale data processing, enabling developer velocity through AI coding assistants and LLMs, developing agentic workflows, and driving infrastructure automation. The engineer will also mentor teams and communicate technical strategies to stakeholders.

Cloud Solution Architect role focused on designing and optimizing Generative AI architectures and autonomous agent systems within Google Cloud Platform. Responsibilities include collaborating with engineering teams, ensuring security and cost optimization, and integrating AI development tools.