AI Enterprise Architect

As Ford accelerates its enterprise-wide digital and AI transformation, the AI Advancement Center is expanding its ability to design, build and deploy secure, high-performing AI platforms that can be reused across business functions and geographies.

As a Principal AI Architect, you will define the architectural vision and technical standards for enterprise AI platforms, connecting strategic business requirements with engineering execution.

You will work across engineering, data, cloud, cybersecurity and business teams to establish scalable patterns for Machine Learning Operations (MLOps), Generative AI, Retrieval-Augmented Generation (RAG), model serving, data processing and AI governance.

This is a senior technical leadership role with significant enterprise influence. Your work will help Ford accelerate AI adoption while improving platform reliability, security, reusability and cost efficiency.

Required

- 8+ years of relevant technology experience, including significant experience designing enterprise-scale distributed or cloud-based platforms.
- Proven experience architecting and deploying AI/ML and Generative AI solutions in production.
- Hands-on architectural experience with capabilities such as: Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- Vector databases/vector search
- Model serving and inference
- Model fine-tuning
- MLOps and model lifecycle management

- Strong knowledge of at least one major cloud platform: Microsoft Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP).
- Deep understanding of distributed systems, microservices and container orchestration using technologies such as Docker and Kubernetes.
- Experience with large-scale data and event processing technologies such as Apache Kafka and Apache Spark, or equivalent platforms.
- Experience designing highly available, fault-tolerant and performance-sensitive production systems.
- Demonstrated ability to influence architecture and engineering decisions across multiple teams.
- Strong communication skills with experience engaging senior technical and business stakeholders.

Preferred
- Experience establishing enterprise AI governance, privacy, security and Responsible AI controls.
- Knowledge of regulatory frameworks relevant to AI and data protection, such as the General Data Protection Regulation (GDPR) and EU Artificial Intelligence Act.
- Experience optimising GPU or accelerator-based workloads and implementing cloud Financial Operations (FinOps) practices.
- Experience working within an AI Centre of Excellence (CoE), enterprise platform organisation, or other central technology function.
- Experience leading enterprise-scale AI adoption or technology transformation programmes.