SpaceX
Application Software Engineer, Applied AI
About this role
SpaceX seeks an Application Software Engineer specializing in Applied AI to design, deploy, and integrate large language models and agentic systems across mission-critical applications. You'll own the complete lifecycle of AI capabilities from prototype to production, working on systems that accelerate launch vehicle production, flight operations, and Starlink infrastructure.
What you'll do
- Develop and deploy AI-powered applications that enhance SpaceX production, flight, and Starlink operations
- Design and evaluate modern LLM systems, agentic workflows, multi-agent orchestration, and advanced retrieval architectures for production use
- Own end-to-end AI system lifecycle including design, evaluation, deployment, monitoring, and iteration
- Build evaluation frameworks (LLM-as-judge, automated benchmarks) and production observability systems for AI quality, safety, and cost
- Partner with Product, Engineering, and Operations teams to identify high-leverage AI opportunities and deliver solutions
- Stay current with emerging LLM techniques and integrate best practices into production systems across SpaceX programs
What they're looking for
- Full-stack software development
- LLM evaluation, deployment, and integration in production systems
- Agentic systems, tool-use, function calling, and multi-agent orchestration
- Python, C#.NET, Go, Scala, Java, or similar programming languages
- Production architecture design with emphasis on reliability and safety
- Docker, Kubernetes, and data streaming platforms (Kafka or similar)
- Database systems (PostgreSQL, SQL Server) and frontend frameworks (React, Angular)
- AI evaluation and observability/monitoring frameworks
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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
- Walk us through a production AI system you've built end-to-end, from prototype to deployment. What were the key challenges and how did you address them?
- Describe your experience with LLM-based evaluation frameworks and monitoring systems. How have you measured AI quality and safety in production?