SpaceX
Software Engineer, Manufacturing Infrastructure
About this role
SpaceX seeks a Software Engineer to develop mission-critical manufacturing and operational software that supports rapid Starship production and Starlink satellite constellation management. You'll own full-stack applications across SpaceX's infrastructure, working closely with cross-functional teams to deliver reliable systems at scale.
What you'll do
- Develop highly reliable, full-stack software solutions used across SpaceX manufacturing and operations
- Create new applications that improve SpaceX's production efficiency and operational capabilities
- Build prototypes to validate design concepts and quantify technical constraints
- Investigate user problems deeply to design and implement efficient solutions
- Participate in architecture, design, and code reviews with collaborative input
- Own all aspects of software engineering and product development from concept to deployment
What they're looking for
- Full-stack software development
- Object-oriented programming (Python, C#.NET, Go, Scala, Java, or similar)
- Single-page web application development (Angular, React, or similar)
- Distributed systems and high-throughput data processing (Kafka, RabbitMQ, ActiveMQ)
- Docker, Kubernetes, and containerization
- CI/CD, version control, and build systems (Bazel, Gradle, Make)
- Database design and SQL (PostgreSQL, SQL Server)
- Linux/UNIX systems, Terraform, Ansible, or similar infrastructure tools
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SpaceX
SpaceX develops advanced spacecraft and satellite systems, including the Starshield government satellite constellation and Starfall re-entry cargo capsule for global delivery. The company is hiring engineers in avionics integration, software test automation, mechanical design, and hardware reliability to validate flight-critical systems and ensure mission success.
- Website
- spacex.com
Likely interview questions
- Tell us about a full-stack application you've built from scratch—what were the key architectural decisions and trade-offs?
- Describe your experience with distributed data processing systems like Kafka or RabbitMQ. How did you handle high-throughput scenarios?