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
