Job Description
Position Summary: Lead the design and implementation of advanced AI solutions, primarily utilizing LLMs for natural-language interaction with enterprise data. This Principal Engineer role involves designing and building production AI applications (including conversational agents and RAG systems) to turn business questions into actionable insights. Expertise in modern LLM framework, embeddings, chunkings, and enterprise integration patterns is required to deliver intelligent, scalable solutions. This client-facing position necessitates communicating complex AI system behaviors to both technical and business leadership. Key Responsibilities: Lead the end-to-end development of advanced AI solutions, including agentic systems, RAG pipelines, and multi-agent workflows Design and implement embedding and chunking strategies essential for effective Retrieval-Augmented Generation (RAG) across enterprise data Create integrations to connect AI agents with enterprise data systems, APIs, and services Develop robust, production-grade asynchronous Python applications with proper error handling and session management Implement vector database and graph database solutions for semantic search and knowledge representation Establish agentic architecture, including data flows, interfaces, and mechanisms across all enterprise systems Deploy and manage AI agents on cloud platforms using CI/CD pipelines, infrastructure as code, and managed AI services Implement monitoring, logging, and observability for agent interactions to guarantee system reliability and support debugging Develop context engineering strategies that assemble dynamic context for consistent and accurate Large Language Model (LLM) behavior Engage with clients to translate business requirements into AI solution architectures, and balance feature development with techn