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Niche agentic-LLM skillset reduces competition despite metro location.
Specialized LLM and agentic AI expertise is required but transferable across AI-focused industries, so medium sensitivity.
Numerous mandatory LLM/MLOps, LangChain, cloud, Python, and vector-database requirements imply high shortlisting strictness.
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Design and develop autonomous AI systems using LLMs, including multi-agent workflows and RAG pipelines for document understanding and data extraction.
Build and maintain APIs and services for AI pipelines using Python and FastAPI.
Evaluate and optimize AI model accuracy, latency, and reliability in real-time applications.
Strong proficiency in Python and SQL.
Experience with LLMs, RAG, multi-agent systems, and frameworks like LangChain or LangGraph.
Experience with vector databases, OCR tools, and deploying models on cloud platforms (Azure preferred).
Work Experience Required: Not explicitly mentioned in the JD.
Hands-on experience with multi-agent AI systems and orchestration frameworks suitable for complex AI workflows.
Practical knowledge of cloud deployments (especially Azure), Docker, and prompt engineering techniques.
Familiarity with real-time AI applications focusing on model performance and scalability.