AI Engineer

As one of our early AI Engineering hires, you'll help define what AI at Cube looks like. You'll build the AI features people actually use from our self-hosted chat interface and MCP server to retrieval pipelines, prompts, evaluations, and integrations with internal systems. You'll work closely with our Infrastructure and Data Engineering teams to design architecture, connect systems, and transform emerging AI capabilities into practical products and tools that solve real problems every day.

• Maintain and tunning our self-hosted chat interface including model connections, MCP integration, RAG/knowledge base setup • Build the RAG pipeline: ingestion, chunking, embeddings, vector store, retrieval, reranking, and evaluation • Integrate LiteLLM or OpenRouter as the gateway; handle routing, fallbacks, rate limits, and cost tracking • Maintain and configure MCP server and the tools it exposes to the model • Write prompts and evaluations, and iterate on them based on real usage and failure cases • Monitoring the logging, tracing, and guardrails of our AI platforms and model does. • Good to have exposure on MLOps/Platform team to deploy self-hosted models (vLLM, TGI, Ollama) and keep them healthy • Ship features end-to-end: API, retrieval, prompt, evaluation, and rollout