Backend Engineer, Enterprise

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars.
SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next.

BACKEND ENGINEER, ENTERPRISE

The Enterprise Agents Engineering Team at SpaceXSI is a team of builders solving the hardest problems in applied AI: integrating with messy systems, orchestrating complex workflows, and harnessing AI to transform business operations. We build full-stack solutions with ownership of end-to-end product execution from ideation to deployment, collaborating closely with our team to incorporate cutting-edge AI advancements into robust and reliable user-centric solutions. Through an iterative development process, we work hand-in-hand with customers to gather feedback, refine features, and evolve products to address real-world challenges.

BASIC QUALIFICATIONS:

• Experience with Rust or C++
• Experience in designing, implementing, and maintaining reliable and horizontally scalable distributed systems

PREFERRED SKILLS AND EXPERIENCE:

• Experience with operating databases such as PostgreSQL, ClickHouse, and CockroachDB
• Knowledge of service observability and reliability best practices
• Expert knowledge of Python
• Expert knowledge of TypeScript
• Experience with Docker, Kubernetes, and containerized applications
• Expert knowledge of gRPC (unary, response streaming, bi-directional streaming, REST mapping)
• Hands-on experience with LLM APIs, embeddings, or RAG patterns
• Track record of delivering user-facing software at scale

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