Summary
Design and deploy AI agents and GenAI solutions using Azure AI services, LangChain, and RAG pipelines to build AI copilots and chatbots for enterprise workflows.
Design, develop, and deploy AI agents and end-to-end GenAI solutions to solve complex business and engineering challenges
Collaborate with domain experts and stakeholders to understand processes and translate requirements into AI-driven solutions
Build and integrate solutions using Azure AI services, including Azure OpenAI, Azure AI Foundry, Azure Machine Learning, AI Search, and Cognitive Services
Develop Retrieval-Augmented Generation (RAG) pipelines, AI copilots, chatbots, and agentic workflows leveraging enterprise knowledge sources
Implement prompt engineering, tool/function calling, workflow orchestration, and multi-agent frameworks using LangChain, Semantic Kernel, or similar technologies
Deploy, monitor, and optimize AI applications in production while ensuring security, governance, scalability, and performance
Establish LLMOps/MLOps practices for model deployment, evaluation, monitoring, and continuous improvement
Requirements
Strong programming skills in Python
Hands-on experience with Azure AI ecosystem (Azure OpenAI, Azure AI Foundry, Azure ML, AI Search, Cognitive Services)
Experience building LLM-based applications, AI agents, RAG solutions, and GenAI-powered applications
Knowledge of prompt engineering, vector databases, semantic search, and orchestration frameworks (LangChain, Semantic Kernel, AutoGen, etc.)
Strong analytical, problem-solving, and stakeholder management skills
Familiarity with cloud-native development, APIs, and MLOps/LLMOps practices