Company Description
High 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 optimize RAG (Retrieval-Augmented Generation) systems on Azure.
- Deploy, fine-tune, and manage LLMs within Azure environments (OpenAI, HuggingFace, or custom models).
- Deep integration with Azure AI Search , Cognitive Services , and Azure 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 with Azure AI Studio / Foundry or Azure OpenAI Service .Proven knowledge of deploying and scaling LLM-based applications .Practical hands-on with vector databases , embedding workflows, and tools like LangChain or Semantic Kernel .Understanding of Power BI semantic models , finance document structures, and business logic.Familiarity with Azure Machine Learning , Azure Functions , and Key Vault for secure orchestration.Python-based AI pipeline development (FastAPI experience is a plus).Good-to-Have Skills :
Familiarity with financial or BI reporting systems (Power BI, QuickBooks, accounting workflows).Experience integrating search + chat UIs (Streamlit, Gradio, React, etc.).Background in building AI copilots or enterprise-focused assistants .Why This Role Matters :
While your Technical Project Lead will guide the overall engineering and system integration, this AI Engineer will :
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.