I'm Nabojyoti Pandey, a data and AI engineer focused on building agentic AI systems, retrieval-augmented generation (RAG) pipelines, and scalable machine learning platforms.
A Microsoft Azure Certified AI Engineer and Kaggle Notebook Expert, I work at the intersection of GenAI, data engineering, and production ML.
Over the past few years, I’ve engineered scalable data pipelines, deployed real-time risk and analytics systems, and built intelligent applications supporting use cases ranging from derivative clearing and HFT backtesting to ML-driven portfolio optimization.
I’m particularly interested in designing reliable, interpretable, and production-ready AI systems, leveraging multi-agent architectures, orchestration frameworks, and cloud-native infrastructure to translate complex data into actionable intelligence.
Built and deployed ML & deep learning models for predictive analytics, portfolio optimization, and NLP applications.
Designed agentic workflows, RAG pipelines, and vector-based retrieval systems for Generative AI applications.
Experienced in software engineering, containerization, and scalable system design.
Built automated CI/CD pipelines, containerized applications, and provisioned cloud infrastructure using GitHub Actions, GitLab CI, Docker, and Terraform for scalable production deployments.
Managed cloud services, relational & NoSQL databases, and deployed AI workloads on multi-cloud environments.
Built scalable ETL/ELT pipelines, batch & streaming data workflows, and interactive analytics dashboards.
An AI-driven multi-agent equity research engine that autonomously gathers financial data, conducts analysis, and generates structured research reports for equities.
🔗 https://github.com/nabojyoti/agentic-equity-research-system
A modular Retrieval-Augmented Generation system integrating agent-to-agent workflows and Model Context Protocol tooling to intelligently route queries, gather knowledge, and generate grounded responses.
🔗 https://github.com/nabojyoti/agentic-rag-a2a-mcp
An autonomous AI assistant for developers that interprets tasks, generates code, and automates engineering workflows to boost productivity and streamline development.
🔗 https://github.com/nabojyoti/ai-dev-agent
An adaptive RAG workflow using LangGraph to dynamically choose retrieval and generation strategies based on query complexity, improving relevance and answer quality.
🔗 https://github.com/nabojyoti/langgraph-adaptive-rag
An automated system designed to generate detailed proposal letters for NGOs. It utilizes prompt engineering, generative AI, and retrieval-augmented generation (RAG) techniques.
A machine learning-powered Flask-based web application designed for product recommendation. It delivers personalized suggestions to users based on their preferences and behaviors.
An end-to-end data engineering project utilizing the IPL dataset. It encompasses data extraction, transformation, and loading processes, leveraging tools like Apache Spark and Snowflake.
- 🎓 Microsoft Certified: Azure AI Engineer Associate
- 📈 Generative AI with Large Language Models, DeepLearning.AI
- 🧠 Kaggle Notebook Expert
I'm always open to collaboration, learning, and new opportunities. Feel free to reach out!
- GitHub: nabojyoti
- Email: nabojyoti.product@gmail.com
- LinkedIn: Nabojyoti Pandey
- Kaggle: kaggle