Gen Ai developer

Role & responsibilities

Responsibilities

• Build end-to-end RAG pipelines: parse chunk embed retrieve generate
• Develop agentic workflows using AgenticX, LangGraph, or custom orchestration
• Parse contract PDFs using layout-aware and OCR-based parsers (Unstructured, PyMuPDF, PDFPlumber)
• Enable multimodal processing (text + images/tables) using models like GPT-4V, LLaVA, Donut
• Integrate open-source models (Mistral, LLaMA3, Ollama) and vector databases (Milvus, FAISS, Qdrant)
• Build modular APIs (FastAPI) for Q&A, summarization, and classification across documents
• Optimize retrieval/generation for long-context and multi-document inputs

Required Skills

• 6+ years in backend/ML; 1+ year in GenAI, RAG, or agentic architectures
• Strong Python skills; experience with LangChain, LlamaIndex, Haystack
• Deep experience in PDF parsing (text, tables, images) and chunking strategies
• Familiarity with multimodal models (e.g., GPT-4V, LLaVA, or equivalents)
• Hands-on with vector DBs, FastAPI, Redis/Postgres
• Understanding of legal/contract structure and NLP challenges