Backend Engineer - Enterprise

SpaceXAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.

About THE Role

The Enterprise Agents Engineering Team at SpaceXAI 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:

• Expert knowledge of either Rust or C++,

• Experience in designing, implementing, and maintaining reliable and horizontally scalable distributed systems,

• Knowledge of service observability and reliability best practices,

• Experience in operating commonly used databases such as PostgreSQL, Clickhouse, and CockroachDB

PREFERRED SKILLS AND EXPERIENCE:

• Expert knowledge of Python,

• Experience with Docker, Kubernetes, and containerized applications,

• Expert knowledge of TypeScript,

• 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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