Job DescriptionThe 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.
Responsibilities1. 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, BigQuery, 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 DevSecOps 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, telemetry, and feedback loops.
- Support low-code or self-service AI capabilities that allow technical and non-technical users to create guided workflows or AI-assisted solutions.
- Explore and apply emerging AI development patterns, including retrieval-augmented generation, agentic workflows, Model Context Protocol, and Agent-to-Agent integration where appropriate.
5. Agile Collaboration and Delivery- Work closely with product owners, designers, data scientists, software engineers, DevOps engineers, and business stakeholders.
- Translate user needs and product requirements into high-quality technical solutions.
- Contribute to backlog refinement, sprint planning, estimation, demos, retrospectives, and delivery planning.
- Use metrics, telemetry, and user feedback to improve application performance, usability, adoption, and business impact.
- Share knowledge with the team on AI-assisted engineering practices, reusable development patterns, and full stack best practices.
QualificationsMinimum Qualifications:- Bachelor's Degree in Computer Science, Software Engineering, Engineering, Information Systems, or a related technical field, or an equivalent combination of education and relevant experience.
- 7+ years of professional software development experience.
- 7+ years of experience building modern web applications using Angular, TypeScript, HTML, CSS/SCSS, and modern frontend engineering practices.
- Experience developing backend services, APIs, and integrations using one or more languages or frameworks such as Node.js, Java, Python, Spring Boot, NestJS, Express, or similar.
- Hands-on experience with Google Cloud Platform or equivalent cloud platform.
- Practical experience using AI coding assistants, generative AI tools, or LLM-based development workflows to accelerate software delivery.
- Understanding of how AI can support the SDLC, including requirements analysis, coding, testing, documentation, debugging, deployment, and operational support.
- Experience with REST APIs, authentication/authorization patterns, secure coding practices, and enterprise application integration.
- Experience with Git, CI/CD pipelines, automated testing, code reviews, and Agile software development practices.
- Ability to write clean, maintainable, well-tested code and troubleshoot complex full stack issues.
- Strong communication and collaboration skills with the ability to work across technical and non-technical teams.
Preferred Qualifications- Experience deploying applications using GCP services such as Cloud Run, GKE, Cloud Functions, App Engine, Cloud Build, Artifact Registry, Cloud Storage, BigQuery, Pub/Sub, Firestore, Cloud SQL, Secret Manager, or Cloud Monitoring.
- Experience with Angular architecture patterns, RxJS, NgRx or other state management approaches, design systems, accessibility, and frontend performance optimization.
- Experience building AI-enabled applications using LLM APIs, embeddings, vector search, retrieval-augmented generation, prompt engineering, or agentic workflows.
- Experience integrating AI capabilities into internal tools, developer platforms, workflow automation, or engineering productivity applications.
- Experience with unit testing, component testing, API testing, and end-to-end testing using tools such as Jasmine, Karma, Jest, Cypress, Playwright, JUnit, PyTest, or similar.
- Experience with containerization and deployment tools such as Docker, Kubernetes, GKE, Terraform, or similar.
- Familiarity with observability tools, application monitoring, logging, tracing, and production support practices.
- Familiarity with Model Context Protocol, Agent-to-Agent communication, LangChain, Semantic Kernel, CrewAI, AutoGen, or similar AI orchestration technologies.
- Automotive, embedded systems, vehicle software, electrical architecture, hardware signals, or product development experience.
- Experience working in regulated or enterprise environments with strong security, privacy, data governance, and compliance requirements.
Desired Technical Skills- Frontend: Angular, TypeScript, HTML, CSS/SCSS, RxJS, NgRx, Angular Material or similar component libraries
- Backend: Node.js, Java, Python, Spring Boot, NestJS, Express, REST APIs, microservices
- Cloud: Google Cloud Platform, Cloud Run, GKE, Cloud Functions, Cloud Storage, BigQuery, Pub/Sub, Cloud SQL, Firestore
- DevOps: Git, Docker, CI/CD, Cloud Build, Artifact Registry, Kubernetes, automated deployments
- AI/LLM: AI coding assistants, prompt engineering, LLM APIs, RAG, embeddings, vector databases, agentic workflows
- Engineering Practices: Agile, secure coding, API design, observability, documentation, production support
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, or a series of new teams and new skills? Will you be a leader, a changemaker, a technical expert, a culture builder...or all of the above? No matter what you choose, we offer a work life that works for you, including:
- Immediate medical, dental, vision and prescription drug coverage
- Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up childcare and more
- Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more
- Vehicle discount program for employees and family members and management leases
- Tuition assistance
- Established and active employee resource groups
- Paid time off for individual and team community service
- A generous schedule of paid holidays, including the week between Christmas and New Year's Day
- Paid time off and the option to purchase additional vacation time.
This position is a range of salary grades 7-8 and ranges from $99,600-$192,900.
Final determination of salary grade will be based on candidate's skills and experience, and base salary will be set within the applicable range according to job scope, responsibility and competitive market value.For more information on salary and benefits, click here: https://fordcareers.co/GSR
Visa sponsorship is available for this position.Domestic relocation is not available for this position.This position is hybrid. Candidates who are in commuting distance to a Ford hub location may be required to be onsite four or more days per week.
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