AI Engineer

AI Agent Development & Integration:

Develop intelligent financial agents using LangChain, LangGraph and related frameworks

Design and implement multi-agent collaborative systems for complex financial workflows

Build intelligent AR/AP automation agents for accounts receivable/payable processing

Develop smart report generation agents for automated financial analysis and data visualization

RAG System Design & Vector Retrieval:

Design and implement RAG (Retrieval-Augmented Generation) systems for financial knowledge bases

Build vector databases for efficient document retrieval and semantic search

Develop embedding model optimization solutions to improve retrieval accuracy and response speed

Integrate multimodal data processing to support various formats including financial documents, invoices, and reports

Document Processing & Multimodal AI:

Integrate OCR technology for intelligent recognition of financial receipts and documents

Develop multimodal model processing solutions for documents, images, tables and mixed data types

Establish document preprocessing and feature extraction pipelines to improve data quality

Integrate with mainstream ERP systems through APIs for real-time data synchronization

AI Model Optimization & Training:

Conduct model fine-tuning and training using PyTorch/TensorFlow frameworks

Utilize Hugging Face ecosystem for model selection and optimization

Optimize agent response quality through Prompt Engineering techniques

Establish model performance evaluation systems for continuous AI system improvement

Ensure all AI systems comply with US financial regulations (SOX, GAAP, etc.)