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 demo
Purpose: Technical evaluation for potential long-term hire
Frontend / UI: None (backend prototype only)
Contact:
Objective
We'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 format
Download materials:
(Benchmark uses unseen questions.)
Deliverable
Implement 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 Demo
In 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.
Evaluation
Passing 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).