SpaceX
Operations Engineer, Applied AI (Application Software)
About this role
SpaceX seeks an Operations Engineer to serve as a technical bridge between internal teams and AI capabilities, helping design and implement large language model solutions across the organization. You'll build prototypes, advise on system architecture, and guide cross-functional teams from early exploration through production deployment while staying current with evolving LLM technologies.
What you'll do
- Partner with internal teams to understand needs and design technical approaches aligned with business goals
- Act as primary technical contact supporting end-to-end LLM integration projects and coordinating across teams
- Build prototypes and proof-of-concept applications demonstrating effective integration with Spok/Grok platforms
- Advise on system-to-system architecture and help teams develop LLM-powered applications
- Stay current with evolving LLM technologies, best practices, and tools in fast-moving environments
- Support Sales, Product, and Engineering teams throughout implementation lifecycle
What they're looking for
- Large Language Models (LLMs) and prompt engineering
- Production-level application development and coding
- LLM techniques: prompt design, evaluation, agent systems, retrieval architecture
- AI product design, integration, and testing
- System architecture and design
- Cross-functional collaboration and stakeholder management
- Enterprise AI system design and process improvement
- Fast-paced problem-solving under pressure
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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
- Describe a production LLM application you've shipped—what were the key technical challenges and how did you solve them?
- Walk us through how you'd approach designing a proof-of-concept to help an engineering team explore LLM integration for their specific workflow.