AI Platform Engineer: Cloud, Data & AI Apps

Ford Motor; Allen Park (MI); Hybrid; USD 100,000 - 167,000; Full time

Benefits offered by this job

Medical, dental, and prescription drug

Tuition assistance

Vehicle discount program

Paid time off

Paid holidays

Job summary

Ford Motor Company is seeking an AI Platform Engineer to design, develop, and deploy software for enterprise AI and analytics platforms. You will build full-stack solutions including web apps, backend services, APIs, platform integrations, data services, and cloud workflows.

The role combines software engineering, cloud infrastructure, data and platform integration, DevSecOps, and production operations, with opportunities to integrate ML and generative AI services into production applications.

Qualifications

• Bachelor’s degree in computer science, information technology or related field; equivalent experience considered.
• Master’s degree in CS/CE or related quantitative field preferred.

Responsibilities

• Design, build, test, and maintain full-stack web applications, REST APIs, and integrations for enterprise analytics and AI platforms.
• Implement AI capabilities: model serving, retrieval, data grounding, and workflow orchestration as needed.
• Design, provision, and manage GCP environments using Terraform with CI/CD-driven workflows.
• Develop data-ingestion, transformation, and service integration components across platforms.
• Collaborate with product, design, data, security, and operations teams in an Agile setting.

Skills

Software engineering

Angular

React

Vue

FastAPI

Flask

Django

Spring Boot

Python

Java

GCP

Terraform

CI/CD

Security practices

Observability

LangChain

LlamaIndex

Education

Bachelor’s degree in CS/IT or related field

Master’s degree in CS/CE or related field (preferred)

Tools

Terraform

GCP

Job description

Ford Motor Company is seeking an AI Platform Engineer to design, develop, and deploy software for enterprise AI and analytics platforms. You will build full-stack solutions including web apps, backend services, APIs, platform integrations, data services, and cloud workflows.

The role combines software engineering, cloud infrastructure, data and platform integration, DevSecOps, and production operations, with opportunities to integrate ML and generative AI services into production applications.