Lead Engineer

• Design and deploy a RAG-based knowledge service, including ingestion pipelines consolidating information from codebases, documentation, and structured data

• Build agentic tooling enabling LLM agents to navigate and reason over large, heterogeneous technical corpora

• Develop pipelines that synthesize knowledge artifacts at multiple levels of abstraction from low-level technical references to functional and business-oriented content

• Define and maintain a domain ontology capturing NeoXam's product concepts and their relationships

• Continuously improve retrieval quality, agent reasoning, and output reliability based on real usage

Why This Problem Is Hard

• Highly heterogeneous inputs: code, documentation, financial data, configurations

• Strong correctness expectations with multi-level reasoning technical, functional, business

• Constantly evolving knowledge across projects and clients

  • Outputs must be explainable and trustworthy not black-box answers