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 into mission-critical production applications that support launch operations and Starlink services. You'll own the full lifecycle of AI capabilities from prototype to production, collaborating with product and engineering teams to solve high-impact problems at scale.
What you'll do
- Design and deploy production AI systems including LLMs, agentic workflows, and tool-use architectures that enhance SpaceX operations
- Own end-to-end AI product lifecycle: prototyping, evaluation, deployment, monitoring, and iteration
- Build evaluation frameworks and production observability systems for AI quality, safety, latency, and cost metrics
- Develop reliable software solutions that accelerate vehicle production, flight operations, and Starlink growth
- Architect scalable systems for multi-agent orchestration, advanced retrieval, and long-context applications with emphasis on safety
- 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 and production system design
- Large language models, agentic systems, and tool-use / function calling
- Python, C#.NET, Go, Java, or similar programming languages
- Docker, Kubernetes, and modern data streaming (Kafka or similar)
- Production evaluation systems and AI observability/monitoring
- Front-end frameworks (React, Angular) and databases (PostgreSQL, SQL Server)
- A/B testing, red-teaming, and responsible AI deployment
- Multi-agent orchestration and advanced retrieval architectures
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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 built from prototype to deployment—what were the key challenges and how did you address reliability and safety?
- Describe your experience evaluating and monitoring LLM quality in production. What metrics do you track and how do you handle model degradation?