AI Engineering Lead

Job-:
Global Data Insight & Analytics

Location:

Dearborn, MI, United States Workplace:
Hybrid

Schedule:

Full time Posted:
Preferred Degree:
Master of Science As the AI Engineering Lead, you will architect, build, and scale AI-powered solutions that accelerate both the delivery of Integrated Services Data, AI & Analytics (ISDAIA) products and the adoption of AI capabilities across the Integrated Services business.

You will lead the development of enterprise-grade AI applications, agentic systems, copilots, retrieval-augmented generation (RAG) solutions, and intelligent workflow automation that transform how teams discover insights, make decisions, and deliver value.

This role combines hands-on technical leadership with product thinking and strategic execution. You will partner closely with Product Managers, Engineering Teams, Analytics Leaders, and Business Stakeholders to identify high-value use cases, develop reusable AI capabilities, and enable responsible AI adoption  will play a key role in shaping the future AI ecosystem for Integrated Services by building scalable frameworks, shared services, and AI-enabled experiences that improve business outcomes, operational efficiency, and speed to delivery.

Qualifications

Minimum Requirements Bachelor’s Degree in a related field (Computer Science, Artificial Intelligence, Data Science, Engineering, Information Technology, or equivalent).5 to 8 years of experience delivering enterprise software, analytics, data, or AI solutions.
5+ years of experience using Python-based development technologies and modern software engineering practices.
3+ years of experience designing, deploying, and supporting AI/ML or Generative AI solutions in production environments.

Experience building and deploying Generative AI, conversational AI, Copilot, or agent-based solutions.

Experience acting as a senior technical lead facilitating solution trade-offs and architectural decisions.

Experience using Cloud AI Platforms (GCP preferred).Strong understanding of APIs, cloud-native architectures, CI/CD pipelines, and enterprise application development.

Hands-on experience with Generative AI technologies, Retrieval-Augmented Generation (RAG), and enterprise AI deployment.

Preferred Requirements Master’s Degree in Artificial Intelligence, Computer Science, Data Science, Engineering, or related field.

Experience managing and growing high-performing AI engineering teams.

Experience developing enterprise copilots, AI assistants, agent-based systems, and intelligent automation solutions.

Experience implementing Retrieval-Augmented Generation (RAG) architectures, vector databases, semantic search, and knowledge-grounding strategies.

Strong working knowledge of GCP and enterprise AI architecture patterns.

Expertise in open-source technologies such as Python, Lang Chain, Lang Graph, Semantic Kernel, SQL, Spark, and modern AI development frameworks.

Experience working with Vertex AI, OpenAI, Anthropic, Gemini, or comparable enterprise AI ecosystems.

Experience building reusable AI platforms, accelerators, frameworks, and enablement capabilities.

Experience deploying AI solutions into business workflows, analytics products, self-service insights platforms, or decision-support solutions.

Experience implementing Responsible AI, AI governance, MLOps, and LLMOps practices at enterprise scale.

You may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!

As an established global company, we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe, or keep you close to home? Will your career be a deep dive into what you love,…