🚀 𝗟𝗼𝗼𝗸𝗶𝗻𝗴 𝘁𝗼 𝗯𝘂𝗶𝗹𝗱 𝗿𝗲𝗮𝗹-𝘄𝗼𝗿𝗹𝗱 𝗔𝗜 𝘀𝘆𝘀𝘁𝗲𝗺𝘀—𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝗱𝗲𝗺𝗼𝘀? 𝗟𝗲𝘁’𝘀 𝗰𝗼𝗻𝗻𝗲𝗰𝘁! 🔍 With 12+ years of experience across GenAI, Data Science, and Data Engineering, I specialize in designing and scaling production-grade AI systems that deliver measurable business impact. I’ve built and led AI solutions across retail, media, IoT, transportation, manufacturing, and fintech, working end-to-end—from problem framing to deployment and monitoring. 🚀 Currently working as a Principal GenAI Scientist in Germany, I focus on agentic AI architectures, LLM-powered decision systems, and multimodal intelligence. My work includes real-time offer orchestration, intelligent product understanding, demand forecasting at scale, predictive maintenance, and recommendation systems running in production on Databricks, AWS, and Azure. 🧠 I’m known for bridging the gap between business strategy and deep technical execution, helping teams move beyond hype to AI systems that are reliable, explainable, and scalable. 🎤 I’m passionate about mentoring, career guidance, and system design discussions, and I enjoy helping engineers, data scientists, founders, and leaders make confident decisions around AI adoption and career growth. 𝗣𝗿𝗼𝗳𝗶𝗹𝗲 𝗦𝘂𝗺𝗺𝗮𝗿𝘆 ▪ 12+ years in Data Science, GenAI, and Data Engineering across global enterprises ▪ Deep expertise in LLMs & GenAI (LLaMA, GPT-4, Claude, Mixtral, Falcon) and agentic workflows ▪ Designed and deployed production AI systems for personalization, forecasting, recommendations, and multimodal intelligence ▪ Strong background in end-to-end ML systems: modeling, MLOps, CI/CD, monitoring, and governance ▪ Dual postgraduate degrees + Honorary Doctorate in Artificial Intelligence ▪ Proven ability to work with product, business, and executive stakeholders 𝗧𝗼𝗼𝗹𝘀 𝗮𝗻𝗱 𝗦𝗸𝗶𝗹𝗹𝘀 ▪ GenAI & LLMs: LLaMA, GPT-4, Claude, Mixtral, Falcon, RAG, FAISS, CLIP, multimodal pipelines ▪ Data & ML: Python, PySpark, SQL, XGBoost, Random Forest, Deep Learning, Time Series ▪ Platforms: Databricks, AWS, Azure, GCP, Delta Lake, MLflow, Kubeflow ▪ MLOps & Engineering: CI/CD, model monitoring, retraining pipelines, streaming & batch systems ▪ Domains: Retail AI, IoT analytics, demand forecasting, recommendations, predictive maintenance