Cloud Platform Software Engineer — Global Connected Vehicle Platform at Ford Global

Department: Enterprise TechnologyEducation: Bachelor's Degree or equivalent

Compensation

$85,400 – $232,700/yr

Setup: Remote
Location: Washington, District of Columbia
Type: Full-time
Level: senior
Posted: Aug 25, 2026

Description

Ford is hiring a Senior Software Engineer to design, develop, deploy, and operate scalable cloud-native microservices and APIs for its Connected Vehicle Cloud Platform. The role owns end-to-end delivery across Java, Spring Boot, AWS or GCP, Kubernetes, Kafka, databases, DevOps, CI/CD, monitoring, and performance testing, and requires 5+ years of relevant professional experience. The position is hybrid, may require onsite work four or more days per week, and offers a base salary range of $85,400 to $232,700; visa sponsorship is not available.

Required Skills

Java
Spring Boot
Kubernetes
AWS
GCP
Kafka
PostgreSQL
CI/CD
TDD
API design
Performance testing

Additional Information

Minimum Education: Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
Required Previous Experiences: 5+ years of professional software engineering experience designing, developing, and operating high-performance cloud-based platforms and microservices.
5+ years of experience in roles requiring expertise in Java and Spring Boot.
5+ years of hands-on experience with cloud-native architectures and Kubernetes.
5+ years of experience building event-driven systems with Kafka and relational or non-relational databases.
5+ years of experience with modern DevOps tools and CI/CD pipelines.
5+ years of experience with clean, maintainable code, TDD, and API performance or load testing.
Preferred Qualifications: Master’s degree in Computer Science or a related technical field.
Experience with advanced GCP or AWS cloud-native tools.
Deep understanding of API gateway technologies and protocols.
Experience with GitOps and advanced deployment strategies.
Experience supporting critical, always-on applications in high-throughput, low-latency production environments.
Ability to make data-informed architectural decisions with imperfect or incomplete data.