Tech Proficiency

As a Principal Data Scientist and AI Engineer, I lead the design and implementation of advanced Agentic AI Engineering solutions, leveraging cutting-edge frameworks like LangChain and LangGraph to architect sophisticated, LLM-powered applications that drive significant real-world impact. My comprehensive expertise spans Machine Learning, Data Engineering, Software Engineering, and DevOps, ensuring seamless, end-to-end development. I have a proven track record of deploying reliable, production-ready AI systems, consistently delivering high-value, go-to-market software.

AI Engineering

LangChain • LangGraph • LangSmith • LLM & SLM • Computer Use Agents (CUA) • OpenAI & DeekSeek Coder V2 • Model Context Protocol (MCP) for Agentic Workflows • Retrieval-Augmented Generation (RAG) • ChromaDB + Pinecone • Azure AI Document Intelligence • AI vision • Browser Use • Open-Source LLM + Hugging Face • Claude Sonnet 4 + GitHub Copilot (vibe coding)

Machine Learning

TensorFlow • PyTorch • Scikit-learn • SpaCy • NLTK for Natural Language Processing (NLP) • Matplotlib • Keras • Seaborn • OpenCV • Pandas • Jupyter • Anaconda

Software Development

Python • .NET/C# • SQL • JavaScript • PHP • Node.js • CLI/Bash programming • YAML

Data Engineering

PostgreSQL • Redis • MongoDB • Apache Kafka • MariaDB • SQL & NoSQL; MSSQL • Snowflake • Azure Blobstore • Vector Databases

DevOps & CI/CD

GitHub • Kubernetes • Docker • Jenkins • Azure Pipelines • Kubernetes Autoscaling • GitHub Actions

Platform & Frameworks

Pydantic AI • CrewAI • Azure AI Foundry • Helicone • Azure Cognitive Services • Azure ML • Apache Airflow • Streamlit • React • FastAPI (Pydantic) • Jupyter/Anaconda (R&D) • GraphQL • Datadog • Azure DevOps • GitHub Copilot • Python Flask • Python Django