AI Engineer (Azure AI Foundry & Generative AI)

3 years

0 Lacs

Posted:1 day ago| Platform: Linkedin logo

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On-site

Job Type

Full Time

Job Description

Role Overview
The AI Engineer is responsible for designing and implementing AI-driven applications and RAG (Retrieval-Augmented Generation) systems using Azure AI Foundry and Microsoft Fabric data sources. The role involves integrating Azure OpenAI, AI Search (Vector DB), and Streamlit frontends to deliver intelligent, contextual user experiences.Key Responsibilities
  • Design, develop, and deploy RAG pipelines combining Azure OpenAI with Azure AI Search.
  • Build and maintain AI Foundry Knowledge Bases integrated with Fabric semantic models and OneLake.
  • Implement embedding models and manage vector indexes for unstructured data retrieval.
  • Develop conversational interfaces or dashboards using Streamlit, Azure App Service, or Copilot for Fabric.
  • Collaborate with data engineers to ensure AI models consume accurate and refreshed datasets.
  • Tune and evaluate LLM prompts, temperature settings, and grounding strategies for enterprise contexts.
  • Integrate Microsoft Purview for metadata lineage, governance, and responsible AI monitoring.
  • Apply security, privacy, and compliance principles for AI systems under PDPA and internal data governance frameworks.
  • Support automation of model retraining and continuous learning pipelines.

Qualifications

  • Bachelor’s Degree in Computer Science, Artificial Intelligence, or related field.
  • 3+ years of experience developing AI or ML-based solutions on Azure or similar platforms.
  • Proficient with Azure OpenAI, AI Foundry, Azure AI Search, and Cognitive Services.
  • Familiarity with Microsoft Fabric, OneLake, and Synapse Data Science Workspace.
  • Strong understanding of LLM orchestration, prompt engineering, and RAG architecture.

Preferred Skills

  • Experience with Copilot Studio, Azure AI Studio, or AI Agent orchestration.
  • Knowledge of data governance and lineage tools (Purview, Key Vault).
  • Prior experience building internal chatbots, AI assistants, or generative document intelligence systems.
  • Experience with Python, LangChain, FastAPI, or Streamlit

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