GraphRAG Developer Challenge – Legal Document Processing (Prototype)
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
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).
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