Role & responsibilities

• Develop and implement enterprise-grade LLM-based applications (e.g., RAG, agents, and copilots) using Azure OpenAI, LangChain, and Semantic Kernel.
• Write high-quality, maintainable, and efficient code in Python, including data processing scripts (potentially with PySpark) and API endpoints.
• Build and optimize RAG (Retrieval-Augmented Generation) pipelines, integrating vector search capabilities using Azure Cognitive Search, FAISS, or similar technologies.
• Collaborate with AI Architects and Product Owners to translate requirements and architectural designs into technical specifications and working code.
• Implement and manage MLOps pipelines for model deployment, monitoring, and lifecycle management using Azure Machine Learning, Azure DevOps, and GitHub Actions.
• Integrate AI models and services with other business applications and data sources using Azure Functions, APIM, Logic Apps, and Service Bus.
• Implement robust testing, debugging, and performance tuning for AI applications to ensure scalability and reliability.
• Mentor junior developers, conduct regular code reviews, and promote development best practices (e.g., TDD, clean code).
• Stay current with the latest Azure AI services and Generative AI techniques, experimenting with new tools and frameworks to drive innovation.

Preferred candidate profile