AI/LLM Developer for OCR, Risk Scoring & Fraud Detection Platform

We are looking for an experienced AI/LLM Engineer to help build the AI layer of an enterprise-grade KYC/KYB verification platform. This is a B2B SaaS application used for identity verification, business verification, fraud detection, risk scoring, and compliance automation. This is NOT a chatbot project. Project Overview The platform allows organizations to upload identity and business documents. The AI system should: Process OCR output Extract structured information Validate document data Detect anomalies Generate fraud signals Generate business risk scores Produce compliance summaries Generate explainable AI reports for compliance officers The application is being built using React, Node.js, MongoDB, PostgreSQL, Redis, AWS, and Hyperledger Fabric. Responsibilities Integrate OpenAI, Anthropic or Google Gemini APIs Build prompt pipelines using LangChain Process OCR output from AWS Textract Convert OCR data into structured JSON Generate fraud explanations Generate compliance summaries Build AI-based validation workflow Design deterministic JSON outputs Optimize prompts for cost and accuracy Work closely with frontend and backend developers AI Features Document Identity Validation Cross-document Matching Missing Field Detection Fraud Signal Generation Business Risk Analysis Compliance Summary Generation AI Explanations Confidence Scores Required Skills Python FastAPI OpenAI API Anthropic Claude Google Gemini LangChain AWS Textract OCR Processing Prompt Engineering REST APIs JSON Schema Validation Docker Git Nice to Have Vector Databases RAG Architecture AWS Services Enterprise AI Multi-tenant SaaS Experience Deliverables AI Service Prompt Architecture OCR Processing Pipeline Structured JSON Extraction Risk Scoring Engine Fraud Detection Logic Compliance Summary Generator Documentation GitHub Commits Integration Support Please Include Previous AI/LLM projects GitHub Profile Portfolio OpenAI or Claude integration experience LangChain experience AWS Textract experience Estimated timeline Availability for technical meetings Note: Detailed architecture and project documentation will only be shared with shortlisted candidates after initial discussion and NDA, if required.