> Markdown version of [/jobs/ext/4321039-software-engineer](https://www.wearedevelopers.com/jobs/ext/4321039-software-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Software Engineer

- **Company:** Ford Motor Company
- **Location:** Dearborn, MI, United States
- **Experience:** Expert
- **Salary:** $115,000.0 - $192,900.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Applications Architecture, Application Performance Management, Build Automation, Automation of Tests, BigQuery, Software as a Service, Cloud Computing, Cloud Computing Security, Cloud Engineering, Software Quality, Data Integration, Programming Tools, Github, Identity and Access Management, Python (Programming Language), Machine Learning, Performance Tuning, Software Engineering, Software Systems, Systems Integration, Data Logging, Google Cloud, Cloud Platform System, Cloud Monitoring, GitHub Copilot, Build Management, Containerization, Kubernetes, Information Technology, Data Analytics, Machine Learning Operations, Api Design, Terraform, Code Restructuring, Devsecops, Docker, Microservices
- **Published:** October 22, 2026
- **Apply:** https://www.techcareers.com/job.asp?id=3472134766&tx=DT11303UTI&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

We are seeking a highly skilled and experienced Senior Software Engineer with a strong background in data analytics to join our team. The ideal candidate will have extensive experience working with Google Cloud Platform (GCP) and related tools, and possess a robust understanding of security management, pipeline and automation development, and Python coding. Additionally, experience in the auto industry is highly valued., * A bachelor's degree in Computer Science, Software Engineering, or a related field.

 * 5+ years of experience in the automotive industry.
 * Strong software engineering experience with Python, API development, and GCP.
 * Hands-on experience with GCP services, including BigQuery, Vertex AI, Cloud Functions, and Artifact Registry.
 * Experience with Terraform, Tekton, GitHub, and CI/CD pipeline automation.
 * Knowledge of cloud security, IAM, and application access controls.
 * Experience building Docker container images and deploying cloud-based applications.

Even Better, You May Have...

 * Experience supporting data science, machine learning, or AI/ML workloads in GCP.
 * Familiarity with Kubernetes, microservices, and cloud-native application architecture.
 * Experience implementing DevSecOps practices and integrating security into CI/CD pipelines.
 * Knowledge of cloud monitoring, logging, troubleshooting, and performance optimization.
 * Experience optimizing cloud applications for scalability, reliability, and cost efficiency.
 * Familiarity with generative AI development tools to improve code quality and engineering productivity.
 * Experience supporting enterprise-scale software solutions within the automotive or manufacturing industry.

## Description

* Develop and Manage Cloud Applications: Design, develop, and deploy software solutions on Google Cloud Platform (GCP), ensuring seamless integration, scalability, and reliability.
 * Support Data Science Teams: Build and maintain cloud infrastructure and application capabilities that enable data scientists to develop and deploy solutions efficiently.
 * Develop and Manage APIs: Build, integrate, and maintain APIs that support data integration, application functionality, and communication between systems.
 * Build Automation Pipelines: Develop and maintain CI/CD pipelines and infrastructure automation using tools such as Terraform, Tekton, and GitHub Copilot.
 * Implement Security Best Practices: Manage identity and access management (IAM), permissions, and security controls to protect applications and cloud environments.
 * Optimize Software Solutions: Refactor code, troubleshoot issues, improve application performance, and support product launches and deployments.
 * Build and Deploy Containerized Applications: Use Docker to build, manage, and deploy container images for scalable cloud-based applications.
 * Leverage GCP Services: Implement and integrate services such as BigQuery, Vertex AI, Artifact Registry, Cloud Functions, Cloud Scheduler, and Secret Manager.
 * Automate Development Workflows: Use Python, GitHub, and modern development tools to improve engineering efficiency, code quality, and deployment processes.