As our AI Lead, you will be the architect and visionary for our next generation of intelligent systems. You won’t just be "prompting"; you will be building robust, production-grade RAG (Retrieval-Augmented Generation) architectures and agentic workflows using Azure AI Foundry. Your goal is to transform complex manufacturing data—from telemetry logs to maintenance manuals—into actionable intelligence.

Key Responsibilities

• Architectural Leadership: Design and deploy end-to-end LLM applications using Azure AI Foundry (formerly Azure AI Studio), ensuring seamless integration with Azure OpenAI, Prompt Flow, and AI Search.

• Manufacturing Solutions: Develop AI use cases specifically for the industrial sector, such as:

  • Predictive maintenance assistants for shop-floor technicians.

  • Automated root-cause analysis (RCA) using unstructured sensor data and historical reports.

  • Supply chain optimization and intelligent document processing for logistics.

• Technical Governance: Establish best practices for LLMOps, including evaluation frameworks (groundedness, relevance, and safety), versioning, and cost management.

• Cross-Functional Collaboration: Act as the bridge between Data Science, DevOps, and Manufacturing stakeholders to translate business pain points into technical requirements.

• Mentorship: Lead a team of engineers, fostering a culture of rapid experimentation and high-code quality.

Required Qualifications

• Azure Mastery: Deep, hands-on experience with Azure AI Foundry, Azure OpenAI Service, and Azure Machine Learning.

• LLM Proficiency: Proven track record of deploying LLMs into production. You should be an expert in RAG patterns, vector databases (like Azure AI Search or Pinecone), and agentic frameworks (LangChain, Semantic Kernel, or AutoGen).

• Programming: High proficiency in Python and experience with API design (FastAPI/Flask).

• Manufacturing Context: (Highly Preferred) Familiarity with industrial data standards (OPC-UA, MQTT) or experience working with IoT-driven data environments.

Bonus Points If You Have:

• Experience with "Small Language Models" (SLMs) for edge computing in factory settings.

• Contributions to open-source AI projects.

• Microsoft Certified: Azure AI Engineer Associate.