Key Responsibilities:
AI Agent Development & Autonomous Systems
- Develop AI/ML-powered autonomous agents using Azure AI Foundry, Azure Agent AI Service, LangGraph, AutoGen, and Semantic Kernel
- Design and implement multi-agent AI workflows with reasoning, goal-driven planning, and adaptive memory
- Utilize Semantic Kernel for long-term memory, function calling, and RAG-based workflows
- Orchestrate and fine-tune AI models in production environments using Azure AI Foundry
LLM & AI Integration in Full-Stack Applications
- Deploy GPT-4, Phi-3, and Hugging Face models on Azure OpenAI for enterprise applications
- Integrate LLM-based services into .NET and Node.js APIs
- Develop AI-powered UIs using React.js, embedding natural language interfaces and AI copilots
- Implement vector search and retrieval with Azure Cognitive Search, Pinecone, and FAISS
Full-Stack AI Application Development
- Build backend AI APIs using .NET Core or Node.js integrated with Azure AI services
- Develop interactive AI-driven frontends using React.js, TypeScript, and Microsoft Fluent UI
- Implement AI-assisted chatbots, copilots, and workflow automation in enterprise applications
- Ensure scalability, performance, and security of AI-powered web applications
Enterprise AI & Microsoft Ecosystem Integration
- Build LLM-driven enterprise copilots for Microsoft 365, Teams, and Power Platform
- Develop AI-powered assistants and chatbots integrating with Microsoft Graph API & Azure AI Studio
- Automate workflows using AI agents in Power Automate and Azure Logic Apps
- Enhance enterprise search and knowledge management using Azure Cognitive Search and vector databases
AI Performance Optimization & Responsible AI
- Optimize LLM token usage, reduce latency, and improve cost efficiency
- Implement prompt engineering, retrieval caching, and fine-tuned model deployment
- Ensure compliance with Azure AI Content Safety, Responsible AI principles, and enterprise AI governance
- Build monitoring and explainability tools to track LLM outputs and mitigate risks
Collaboration & AI Strategy
- Collaborate with Data Scientists, Software Engineers, and Cloud Architects for AI-driven solutions
- Advocate for multi-agent AI engineering and AI-assisted application development best practices
- Stay updated with Azure AI innovations and enterprise AI trends
- Contribute to open-source AI projects and Microsoft AI research initiatives
Preferred Qualifications:
- Microsoft AI Certifications (Azure AI Engineer Associate, AI-102, DP-100)
- Experience with multi-modal AI models, LLMOps, and Reinforcement Learning from Human Feedback (RLHF)
- Background in cognitive architectures, explainable AI (XAI), and enterprise AI governance
- Contributions to open-source AI frameworks (LangGraph, AutoGen, Semantic Kernel, Transformers)
