AI-Accelerated Full Stack Software Development Engineer

We made history and now we work to transform the future - for our customers, our communities and our families. You'll see your work on the road every day, helping people move freely and pursue their dreams. At Ford, you can build more than vehicles. Come build what matters.

Enterprise Technology plays a critical part in shaping the future of mobility. If you're looking for the chance to leverage advanced technology to redefine the transportation landscape, enhance the customer experience and improve people's lives, this is the opportunity for you. Join us and challenge your IT expertise and analytical skills to help create vehicles that are as smart as you are.

The VSSE (Vehicle Software and Systems Engineering) team is advancing Ford's use of artificial intelligence across vehicle engineering and product development. We are looking for a Full Stack Engineer who can use AI to accelerate software delivery across the full Software Development Lifecycle (SDLC), from requirements analysis and solution design to development, testing, deployment, monitoring, and continuous improvement.

In this role, you will design, build, and maintain secure and scalable web applications using Angular and cloud-native services on Google Cloud Platform (GCP). You will apply AI-assisted development practices to improve productivity, code quality, test coverage, documentation, and delivery speed while helping transform early-stage AI prototypes into secure, production-ready enterprise applications.

The ideal candidate is a hands-on engineer with strong full stack development skills, practical experience using AI coding assistants and generative AI tools, and the ability to build modern, reliable applications that serve Ford engineering teams at scale.

Full Stack Engineer - AI-Accelerated Software Development:
The VSSE (Vehicle Software and Systems Engineering) team is advancing Ford's use of artificial intelligence across vehicle engineering and product development. We are looking for a Full Stack Engineer who can use AI to accelerate software delivery across the full Software Development Lifecycle (SDLC), from requirements analysis and solution design to development, testing, deployment, monitoring, and continuous improvement.

1. Full Stack Application Development

* Design, develop, test, and maintain full stack web applications using Angular, modern backend services, APIs, and cloud-native technologies on GCP.

* Build responsive, intuitive, and performant user interfaces that simplify complex engineering workflows.

* Develop backend services, RESTful APIs, data integrations, and reusable components to support AI-enabled applications.

* Integrate applications with enterprise data sources, authentication systems, engineering tools, and AI services.

* Ensure applications are secure, scalable, reliable, observable, and maintainable in production environments.

* Participate in architecture reviews, technical design discussions, code reviews, and production readiness assessments.

2. AI-Accelerated Software Development Across the SDLC

* Use AI coding assistants and generative AI tools to accelerate software development, refactoring, debugging, documentation, and code reviews.

* Apply AI to support requirements analysis, user story refinement, acceptance criteria generation, design exploration, and technical documentation.

* Leverage AI to generate and improve unit tests, integration tests, end-to-end tests, regression tests, and test data.

* Use AI-assisted approaches for defect triage, log analysis, root-cause investigation, and production support.

* Identify opportunities to automate repetitive SDLC activities and improve developer productivity.

* Promote responsible and secure use of AI tools while protecting Ford data, intellectual property, and enterprise standards.

3. Cloud-Native Engineering on GCP

* Build, deploy, and support applications using Google Cloud Platform services and cloud-native architecture patterns.

* Work with GCP services such as Cloud Run, Cloud Functions, App Engine, GKE, Cloud Storage, Pub/Sub, Firestore, Big Query, Cloud SQL, Secret Manager, Cloud Build, Artifact Registry, and Cloud Monitoring, as applicable.

* Support CI/CD pipelines, automated testing, containerization, infrastructure automation, and environment management.

* Collaborate with Dev Sec Ops  and platform teams to improve deployment reliability, scalability, performance, and observability.

* Apply cloud security best practices, including identity and access management, secrets management, network controls, and data protection.

4. AI Tool and Platform Integration

* Help build and enhance AI-enabled applications that support Ford Product Development teams across electrical, software, and vehicle systems domains.

* Integrate applications with LLMs, AI APIs, retrieval systems, vector databases, enterprise knowledge sources, and workflow automation tools.

* Contribute to reusable AI platform capabilities such as prompt templates, AI service wrappers, evaluation workflows,…