SpaceX
Application Software Engineer, Applied AI
About this role
SpaceX seeks an Application Software Engineer to design and deploy AI systems—including large language models and agentic workflows—that power production and flight operations. You will own the complete lifecycle of AI capabilities from prototype to production, working across mission-critical applications for launch vehicle manufacturing and Starlink infrastructure.
What you'll do
- Develop reliable AI-powered software solutions for SpaceX production, flight, and Starlink operations
- Own the full lifecycle of Applied AI systems: design, evaluation, deployment, monitoring, and iteration
- Design and architect production systems for agentic workflows, multi-agent orchestration, tool-use, and advanced retrieval with focus on reliability and safety
- Build evaluation frameworks and production observability systems for AI quality, safety, latency, and cost monitoring
- Uncover high-leverage AI opportunities by understanding user problems and delivering efficient, production-grade solutions
- Stay current with emerging LLM techniques and rapidly integrate best practices into SpaceX production systems
What they're looking for
- Large language models and agentic systems
- Full-stack AI product development and deployment
- Python, C#.NET, Go, Java, or similar programming languages
- LLM techniques: tool-use, multi-agent orchestration, advanced retrieval, fine-tuning, structured outputs
- Production AI evaluation and monitoring systems
- Docker, Kubernetes, and data streaming platforms (Kafka)
- Frontend frameworks (React, Angular) and database systems (PostgreSQL, SQL Server)
- System design and production architecture
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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 an end-to-end AI product you've shipped to production—what were the key challenges and how did you address them?
- Describe your experience building evaluation and monitoring systems for LLMs in production. How do you measure AI quality and safety?