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.

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 Open Shift 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.

• Backend services and APIs. Build and maintain REST APIs and microservices in Java and Spring Boot, backed by SQL databases and Big Query.
• Frontend apps and dashboards. Build features and reusable components in React or Angular with Type Script 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 Open Shift 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 (Git Hub 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 Git Hub 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.

• 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.

• GCP experience, especially Cloud Run, GKE, Big Query, Pub/Sub, Cloud SQL, or Cloud Storage.
• Kafka or Pub/Sub, or concepts such as retries, dead-letter queues, and message ordering.
• Open Shift or Kubernetes (deployments, config maps, secrets, health checks).
• CI/CD with Git Hub Actions, Tekton, or Jenkins, code scanning tools such as Sonar Qube, 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