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Description: Role Overview: Hands-on developer responsible for implementing prompt workflows, data chunking, and maintaining the accuracy of AI outputs. Requirements: Required Skills & Qualifications - Tech Stack: Strong Python programming, familiarity with APIs (OpenAI, Anthropic), basic LangChain/LlamaIndex usage. - Qualifications: Bachelor’s in CS or related field; 3–4 years software or data engineering experience with demonstrated exposure to LLM APIs. Responsibilities: Key Responsibilities - Implementation: Build and test basic to intermediate RAG systems using frameworks like - LangChain or Autogen. - Data Processing: Write Python scripts for PDF/document parsing, text chunking, and embedding generation. - Prompt Engineering: Systematically test and version-control system prompts to achieve reliable model responses.