AI Engineer

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)