AI-Driven B2B Lead Generation System

Job ID: 40083224

Budget: $250 – $750 USD

I’m looking for an experienced developer to build an end-to-end AI-driven Python automation system for B2B lead generation, enrichment, filtering, and ICP scoring, with a strong emphasis on accuracy, cost efficiency, and reliability.

The system should take a small set of ideal example companies together with a written ICP, automatically identify lookalike companies, filter out low-quality leads early, deeply enrich only the strongest candidates, and output a ranked CSV of qualified leads.

The solution must be reusable across multiple B2B industries and not hard-coded to a single niche.

I’m open to alternative architectures or implementation approaches if they demonstrably reduce cost, improve scoring accuracy, or increase system robustness.

The intended design and requirements are explained in the attached PDF. I have attempted to build this system myself using Cursor, but the current version is not cost-efficient and has flaws in the scoring logic. That implementation can be shared as additional context if useful.

Max API budget is 200$/m

Timeline is important — I’m aiming to have an initial working version delivered within 1–2 weeks.