I’m moving our income-tax practice toward full automation and need an experienced developer to take the first production block from concept to running code. The piece you’ll tackle is the drafting engine: given structured tax fact patterns and memo outlines in strict JSON, the system should orchestrate LLM + RAG components, enrich the content, and return a clean, review-ready memo draft—also wrapped in JSON. The orchestration layer must run in Prefect and allow easy chaining with future blocks (risk-checking, context expansion, wrapper improvements). I already have preliminary prompts and retrieval sources; your job is to wire them together, build the enrichment tasks, and expose a simple API endpoint so my team can drop a JSON file in and receive the drafted memo back. Key expectations • Use Prefect for flow control and retry logic • Integrate an LLM of your choice (OpenAI, Anthropic, etc.) plus RAG retrieval against my knowledge base (Postgres + pgvector) • Preserve every incoming JSON field, adding only the generated memo content and metadata • Keep the codebase modular so later blocks can plug in without refactor-pain I’ll test by feeding sample returns and verifying that: 1. The flow executes end-to-end without manual steps. 2. Output JSON validates against the provided schema. 3. The draft reads coherently and follows my outline sections exactly. If you’ve built similar Prefect or tax-domain NLP pipelines, that’s a big plus—please mention it when you bid along with an estimated timeline for this first block.