Design, develop, test, and deploy AI-powered applications and services.
Build and optimize LLM and generative AI solutions using Azure OpenAI and related platforms.
Develop RAG architectures that connect LLMs to enterprise documents, databases, APIs, and other data sources.
Design and implement vector search, embeddings, semantic search, and knowledge retrieval capabilities.
Develop AI workflows using frameworks such as Semantic Kernel, LangChain, LangGraph, or Microsoft Copilot Studio.
Integrate AI solutions with existing enterprise applications, APIs, databases, and data platforms.
Develop production-quality services using Python and/or .NET/C#.Work with Azure services including Azure OpenAI, Azure AI Foundry, Azure AI Search, Azure Functions, Azure Storage, and related cloud services.
Build data pipelines and preprocessing workflows to prepare enterprise information for AI applications.
Evaluate LLM performance, accuracy, relevance, latency, and cost.
Implement techniques such as prompt engineering, grounding, retrieval optimization, evaluation, and guardrails.
Partner with data engineers, software engineers, architects, and business stakeholders to move AI initiatives from proof-of-concept to production.
Establish appropriate practices for security, responsible AI, data privacy, and governance.
Troubleshoot and optimize AI applications in production environments.
Stay current with emerging AI technologies, models, frameworks, and development practices.