Summary: This role involves developing and deploying machine learning models, building AI solutions with LLMs and RAG, designing Agentic AI platforms, and implementing data pipelines. Highlights: 1. Develop and deploy advanced machine learning and AI solutions. 2. Build innovative chatbot solutions using LLMs and RAG. 3. Design and build cutting-edge Agentic AI platforms. **Key Responsibilities:** • Develop and deploy machine learning models for predictive analytics, fraud detection, and time series forecasting. • Build chatbot solutions using LLMs (OpenAI, Mistral AI) integrated with RAG, and vector databases. • Design and build an Agentic AI platform with protocols like Agent to Agent (A2A) and Model Context Protocol (MCP) • Implement data pipelines using Databricks, Airflow, and Azure services • Conduct A/B testing and hypothesis testing for product pricing and optimization. • Automate reporting processes and improve operational efficiency through advanced analytics. * Mentor junior team members and contribute to knowledge sharing. \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Required Skills: • Programming: Python, PyTorch, TensorFlow, FastAPI, Node.js, Java is a plus • ML AI: Generative AI, LLMs, NLP, LangChain, LangGraph, knowing Semantic Kernel, Microsoft Agent Framework, Agent Development Kit (Google) is a plus • Data Engineering: Spark, PySpark, DataBricks, Airflow • Databases: Neo4j, Pinecone, BigQuery • Cloud Platforms: Azure (AI Foundry) • MLOps: MLFlow, Kubernetes, Docker • Tools: Looker, Data Studio, Streamlit