AI Engineer – Azure AI Specialist

3 weeks ago

Guntur, India High Volt Analytics Full time

Company DescriptionHigh Volt Analytics assists medium to large organizations in becoming AI ready, starting with Finance & Accounts automation. We focus on automating financial processes to deliver real-time insights and error-free reports, integrating data into a secure AI-ready foundation, offering interactive AI-powered insights, and developing enterprise AI roadmaps. Our clients include CFOs, Controllers, FP&A leaders, and CEOs who aim to move beyond manual processes and harness AI-driven competitive advantages.Core Focus Areas :Build and optimizeRAG (Retrieval-Augmented Generation)systems on Azure. Deploy, fine-tune, and manageLLMswithin Azure environments (OpenAI, HuggingFace, or custom models). Deep integration withAzure AI Search ,Cognitive Services , andAzure Machine Learning pipelines . Collaborate on vector store (Qdrant / Azure AI Search), embeddings, and prompt orchestration. Translate finance data structures into meaningful, conversational AI outputs. Must-Have Skills :Strong experience withAzure AI Studio / FoundryorAzure OpenAI Service . Proven knowledge of deploying and scalingLLM-based applications . Practical hands-on withvector databases , embedding workflows, and tools likeLangChainorSemantic Kernel . Understanding ofPower BI semantic models , finance document structures, and business logic. Familiarity withAzure Machine Learning ,Azure Functions , andKey Vaultfor secure orchestration. Python-based AI pipeline development (FastAPI experience is a plus). Good-to-Have Skills:Familiarity withfinancial or BI reporting systems(Power BI, QuickBooks, accounting workflows). Experience integratingsearch + chat UIs(Streamlit, Gradio, React, etc.). Background in buildingAI copilotsorenterprise-focused assistants . Why This Role Matters: While yourTechnical Project Leadwill guide the overall engineering and system integration, thisAI Engineerwill: Specialize in the AI layer , handling model workflows, retrieval systems, and Azure-based intelligence. Bridge the gap between business data and conversational output , enabling smarter responses. Accelerate integration with Azure-native AI tools , reducing friction and increasing speed-to-market.

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