Simpliigence

• Architect and ship production-grade LLM applications • Design RAG pipelines that actually work at scale • Collaborate closely with product and engineering to own problems end-to-end • Design, build, and deploy AI models, tools, and agents • Partner with the Head of Data & AI to define the technical architecture • Implement retrieval augmented generation (RAG) pipelines • Design and implement Model Context Protocol (MCP) integrations • Build and maintain MCP servers • Establish patterns for MCP host/client configuration, access control, and observability • Implement MLOps and LLMOps practices • Collaborate with data engineers and platform teams