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Tier-1 employer but specialized GenAI skillset reduces candidate pool, producing moderate competition.
GenAI technical skills are transferable across industries but require ML and vector DB expertise.
Specialized GenAI, RAG, vector DB, and multimodal requirements create strong technical filtering.
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Develop end-to-end Retrieval-Augmented Generation (RAG) pipelines including parsing, chunking, embedding, retrieval, and generation.
Build agentic workflows using AgenticX, LangGraph, or custom orchestration frameworks.
Integrate multimodal processing and open-source AI models with vector databases; build modular APIs for document Q&A, summarization, and classification.
Bachelor of Engineering degree required.
Experience with AI/ML, specifically in Generative AI development and working with models like GPT-4V, LLaVA, or similar.
Familiarity with OCR and layout-aware PDF parsers such as Unstructured, PyMuPDF, PDFPlumber.
Location requirement: Bengaluru, India.
Experienced in building scalable AI pipelines involving multi-modal data (text, images, tables) and integrating multiple AI models.
Comfortable with open-source AI frameworks and technologies including vector databases (Milvus, FAISS, Qdrant).
Skilled in developing modular APIs and orchestrating complex workflows using agentic frameworks like AgenticX or LangGraph.