data engineering , Technical Leadership, python, Pytorch, Deep Learning, Machine Learning, Numpy, MLops, Azure, retrieval-augmented generation, vector search, langchain, mentorship, model deployment, embeddings, langgraph, llmops, agentic ai, production integration, model serving, prompt engineering, pipeline architecture

Sql, Microsoft 365, Tableau, Pandas, Power Bi, Power Automate, Git, Flask, Github, Numpy, FastAPI, Python, Azure, Pytest, Docker, Claude, OpenAI, LlamaIndex, Google, Gemini, n8n, LangChain, Anthropic GPT, Pinecone, LangGraph, Zapier, Power Apps, Microsoft Copilot Studio, Sharepoint, Azure AI Search, requests, Dataverse, FAISS

Python, Knn, Neural Networks, SAS, Aws Cloud, Hadoop, Coding, Clustering, Hive, Tensorflow, Random Forest, Scala, Spark, Simulation, anomaly detection, Statistical methods, HDFS, Boosting Trees, Machine learning techniques, scenario analysis, GLM Regression, Teradata

Python, API design, Orchestration, tool calling, planning, explainability requirements, output parsing, parallel tool execution, stateful workflows, contextual compression, agent orchestration, query decomposition, context management, evaluation and testing frameworks for LLM-powered applications, search conversational AI, RAG patterns, multi-index routing, model governance, agentic architectures, cost token management, LLM capabilities and limitations, AWS cloud services, microservices architecture, prompt engineering, workflow automation, retrieval systems

Asynchronous programming, Typescript, Node.js, Python, Databases, Go, Arize, distributed systems design, LLM observability, Langfuse, LlamaIndex, clean API contracts, OpenTelemetry, production tracing frameworks, vector search architectures, agentic orchestration patterns, AutoGen, Caching, CrewAI, Generative AI, LangGraph