I am a Production AI & Full Stack Engineer specializing in building scalable, real-world AI systems automate complex workflows and drive measurable business impact. I design and deploy autonomous AI agents and workflow orchestration systems, integrating LLMs with internal tools, APIs, and business platforms. One of my implementations connects Slack, Notion, and internal APIs with LLM-driven agents, reducing support response time by over 60% while improving consistency and scalability. I have extensive experience developing production-grade RAG systems, combining vector databases, hybrid retrieval, and custom ranking logic to deliver accurate, context-aware responses. My focus is not only on building RAG, but also on evaluation, reliability, and hallucination mitigation in real-world environments. Beyond text-based AI, I build multimodal AI pipelines: - Image AI: scalable tagging and moderation systems using CLIP and YOLOv8 on AWS (Lambda, S3), processing large volumes of content in real time - Voice AI: end-to-end ASR/TTS systems using Whisper and modern neural voice models, enabling conversational and personalized voice interfaces I also specialize in AI system optimization, including cost control, latency reduction, caching strategies, and model selection for production scalability. My strength lies in bridging LLMs with real-world systems, transforming AI capabilities into reliable, production-ready solutions that businesses can depend on. If you need my help, please contact here.