Full Stack Software Engineer

In this position....

Ford's connected vehicles send us a constant stream of data: trips, alerts, battery and health signals, and much more. The Connected Vehicle Data Team in GDIA (Global Data Insight & Analytics) builds the services, APIs and applications that make that data easy to find, understand, and use across Ford.
We're looking for an early- to mid-career full-stack software engineer who likes building things end to end: backend services in Java and Spring Boot, frontends in React or Angular, and the cloud deployments and data flows that connect them. You'll deploy to OpenShift and Google Cloud, learn how streaming data behaves at very large scale, and see your work used to spot vehicle issues sooner.
You don't need to have done everything on this page. We care more that you're curious, careful with details, and eager to learn. That's what the Ford OS Behaviors are about: be a builder, play to win, and deliver the promise.

Qualifications

You’ll have…

• A bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related field.
• 1 to 4 years of professional software engineering experience. Strong internships or co-ops count.
• Hands-on experience building backend services or REST APIs in Java with Spring Boot.
• Working knowledge of SQL and relational databases.
• Day-to-day use of Git, and experience writing automated tests (for example, JUnit).
• A basic understanding of Docker and deploying applications to a cloud or container platform.
• The habit of asking "how will I know this works?" and testing before you ship.

Even better, you may have….

• GCP experience, especially Cloud Run, GKE, BigQuery, Pub/Sub, Cloud SQL, or Cloud Storage.
• Kafka or Pub/Sub, or concepts such as retries, dead-letter queues, and message ordering.
• OpenShift or Kubernetes (deployments, config maps, secrets, health checks).
• CI/CD with GitHub Actions, Tekton, or Jenkins, code scanning tools such as SonarQube, Checkmarx, or FOSSA, and some Terraform.
• Monitoring with Cloud Monitoring, Dynatrace, Grafana, or Splunk, and setting reliability targets (SLOs).
• Agile practices such as Scrum, XP, test-driven development, or pair programming.
• Hands-on work with AI, such as calling an LLM API, building a small RAG app, or an agent. School, hackathon, and personal projects all count.
• Python for scripting or data work.
• Experience with IoT, telemetry, or other time-series data.

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 child care 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 salary grade 6 and ranges from $85,400-$143,200.

This position is a salary grade 7 and ranges from $99,600-$166,600.

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:

Visa sponsorship is not available for this position.

Candidates for positions with Ford Motor Company must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire.

We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status. In the United States, if you need a reasonable accommodation for the online application process due to a disability, please call 1-888-336-0660.

This position is hybrid with a requirement to be onsite four or more days per week.

#LI-Hybrid

#LI-VO1

Responsibilities

What you’ll do….

• Backend services and APIs. Build and maintain REST APIs and microservices in Java and Spring Boot, backed by SQL databases and BigQuery.
• Frontend apps and dashboards. Build features and reusable components in React or Angular with TypeScript that help people explore vehicle data.
• Streaming integrations. Write Kafka and Pub/Sub producers and consumers, and learn how to handle retries, failed messages, and message order.
• Cloud deployments. Package apps with Docker and deploy them to OpenShift and GCP (Cloud Run, GKE), including configuration, secrets, and health checks.
• Testing and quality. Write unit and integration tests with JUnit and frontend test tools (for example, Jest or Cypress), take part in code reviews and pairing, and learn test-driven development.
• Monitoring and support. Add logging, alerts, and dashboards in Cloud Logging and Cloud Monitoring, and help troubleshoot production issues using runbooks.
• Good engineering habits. Use Git and CI/CD (GitHub Actions, Tekton), keep dependencies up to date, fix issues found by code quality and security scans, and follow secure coding, API security, and data privacy practices.
• AI in practice. Use tools like GitHub Copilot every day for code, tests, and documentation. You'll also help with the team's AI work, for example:
  • building the API and UI for an assistant that answers plain-English questions about vehicle data
  • calling LLM APIs to draft metadata, summaries, or release notes
  • trying simple ways for an AI assistant to answer questions from team documentation
  • writing test cases that check AI output is accurate and safe
• Working as a team. Work with senior engineers, the team's technical lead (Anchor), product owners, data engineers, and platform teams to plan work in small pieces and ship them. data engineers, and platform teams to plan work in small pieces and ship them.