GraphRAG Developer Challenge – Legal Document Processing (Prototype)Role: Senior RAG Systems Developer (Contract/Freelance)Compensation: $600 — paid only if you pass (> 95% benchmark)Timeline: 3–5 days from materials receipt to live demoPurpose: Technical evaluation for potential long-term hireFrontend/UI: None (backend prototype only)Contact: ObjectiveWe’re seeking an expert in graph-based retrieval (GraphRAG) to build a high-accuracy prototype for legal document reasoning. This is a paid technical test that may lead to a long-term position. The goal is a true GraphRAG system featuring explicit knowledge-graph construction and traversal, multi-hop reasoning, agentic orchestration, and strong focus on retrieval accuracy and explainability.Materials Provided/docs/ → Pre-processed Markdown legal documents with metadata/sample_questions.Json → Example question format/sample_answers_rag.Json → Example answer formatDownload materials: (Benchmark uses unseen questions.)DeliverableImplement two functions in Python 3.12 (Poetry project):def ingest(document_paths: List(str)) -> None: """Ingest Markdown docs and build the knowledge graph."""def query(questions: List(str)) -> List(str): """Return answers with Vancouver-style citations grounded in retrieved sources."""Requirements: No UI, no API keys provided. Any stack may be used. query(...) must support parallel execution (~400 questions in ≤60 min) and show a progress indicator. Test thoroughly for correctness and performance before the demo.Live DemoIn a 60-minute live session you will:Receive ~400 unseen questions.Run query(...) to produce /answers.Json.Explain your architecture: how the graph is built, traversed, and used to generate grounded answers.Only the developer(s) who wrote the code may present.EvaluationPassing requires an overall score above 95%, measured by (LLM as a judge): Faithfulness (grounded, no hallucinations), Relevance (retrieval matches intent), Completeness (covers key legal points), and Clarity (structured, legally coherent writing).