About
Design and manage end-to-end RAG pipelines for enterprise AI applications Lead the preprocessing of unstructured data, including classification, cleansing, and metadata enrichment Develop and optimize document chunking, embedding, and vectorization strategies
Required Qualifications
Bachelor's degree in Computer Science, Data Engineering, AI/ML, or related field and 8+ years of relevant experience Hands-on experience designing and implementing RAG architectures in production environments Experience working with unstructured data (e.g., PDFs, documents, images) Strong proficiency in Python and experience with NLP/LLM frameworks Experience building scalable data pipelines in cloud environments (AWS, Azure, or GCP)
Languages
- English
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