AI Engineer | LLM Systems, RAG Pipelines & Intelligent AI Solutions

Develop and enhance intelligent AI solutions using **Large Language Models (LLMs), Generative AI, Retrieval-Augmented Generation (RAG), and AI-driven automation** to solve real-world business challenges. Focus on building scalable AI-powered systems that improve operational efficiency, streamline complex workflows, automate repetitive tasks, and enable smarter, data-driven business operations. Design and implement **AI agents, agentic workflows, multi-agent systems, and LLM orchestration** to support autonomous task execution, tool calling, contextual reasoning, and seamless integration with business applications. Implement RAG pipelines, semantic search, vector databases, embeddings, knowledge retrieval, and context-aware AI capabilities to build reliable systems that can work with business data and deliver relevant, actionable results. Build robust AI architectures with **Model Context Protocol (MCP), API integrations, AI tool orchestration, backend services, and intelligent workflow automation**. Integrate AI models and external systems to enable secure data exchange, connected tools, automated business processes, and extensible AI capabilities. Focus on prompt engineering, structured outputs, context management, error handling, and evaluation to improve the accuracy, consistency, and reliability of AI-powered applications. Develop and optimize production-ready AI systems with an emphasis on scalability, performance, maintainability, and business value. Apply modern AI engineering practices across system architecture, workflow design, integration, testing, and deployment to transform business requirements into practical, intelligent software solutions that support automation, productivity, and long-term growth.