Azad manik pantawane Full stack development
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Are you struggling to learn Python, Django, React, or AI the right way? I've been there — and after 5+ years of building real products used by enterprise clients, I now teach the way I wish someone had taught me: by building real projects, not watching tutorials.
What I teach:
Python & Django — From basics to production-ready REST APIs, database design, authentication, deployment on AWS/Azure. I've built e-commerce platforms, job portals, and learning management systems using Django.
MERN Stack (MongoDB, Express, React, Node.js) — Component architecture, state management with Redux, RESTful APIs, and full-stack project development. I've shipped multiple React frontends integrated with backend services.
Generative AI & LLM Engineering — This is where I work daily. I build agentic AI systems using LangChain, LangGraph, RAG pipelines, vector databases, and OpenAI/Claude APIs for enterprise clients. I can teach you prompt engineering, fine-tuning, building AI chatbots, and deploying AI-powered applications — with real code, not just theory.
My teaching style: Every session is project-driven. You'll write code, debug errors, and build something you can show in interviews. I explain the "why" behind every concept so you actually understand, not just memorize.
Who should reach out:
— Beginners who want a structured learning path
— Developers looking to add AI/GenAI skills to their profile
— Students preparing for job interviews or building portfolios
— Anyone tired of tutorial hell who wants to actually build things
I'm currently working as an AI Engineer at a consulting firm, so everything I teach comes directly from what the industry actually needs today. Let's build something together.

Subjects

  • HTML, CSS, and JavaScript Expert

  • MERN Stack Expert

  • Python Django Expert

  • Gen AI Expert

  • LangGraph Expert

Experience

  • ai engineer (Jan, 2025–Present) at Applied AI Consulting LLP in pune
    Architected and developed end-to-end feedback observability pipeline using Python, Langfuse SDK, implementing trace-based feedback linking with dual storage (Langfuse) to enable real-time conversation quality monitoring and user feedback aggregation across specialized AI agents
    Designed and implemented AI-powered offer creation and update pipeline using Python, LangGraph and LangChain, building reusable tools with LLM integration, SOF schema validation, and reference offer processing that reduced manual offer creation time from hours to minutes
    Built a multi-modal offer search system combining SQL-based querying and vector embeddings with LangChain SQL agents, enabling semantic search across financial attributes, multi-bank filtering, and paginated results that improved offer discovery speed by 10x
    Built frontend using React with dynamic filtering, pagination, multi-bank search, and real-time offer status tracking, integrated REST API endpoints
  • full stack developer (Aug, 2020–May, 2025) at iTpreneur Pune
    Architected and developed end-to-end AI-powered automation platforms across financial, organizational, and customer service domains using Python, Django, React, and LangGraph. Built a multi-domain AI Agent Service Toolkit that processes bank statements, tenant registers, and mortgage documents using AWS Textract for structured data extraction. Designed LangGraph-based agent workflows for sequential validation, transformation, and storage of financial data into PostgreSQL via Django ORM. Enabled natural language-driven financial analysis and automated Excel report generation for real estate use cases.

    Developed dynamic reporting systems generating monthly financial, rolling payment, and cash flow reports with Excel template preservation and validated SQL execution, reducing manual reporting effort by 80%. Implemented data integrity mechanisms including duplicate detection, soft deletes, overwrite confirmation flows, and audit logging to ensure traceability and prevent data corruption.

    Engineered RAG pipelines using ChromaDB for semantic search across documents and Slack data with structured metadata indexing. Built automated ingestion systems for PDF, DOCX, and Google Docs with incremental embedding updates and stateful workflows. Developed an AI-powered Slack engine generating meeting summaries and threaded responses, improving reporting efficiency by 70%.

    Designed and deployed full-stack applications including LMS, E-commerce, and Job Management systems using React, Tailwind CSS, Django REST Framework, MySQL, and PostgreSQL. Implemented secure APIs, RBAC, payment integrations, dynamic search, messaging systems, and optimized deployments on Azure and AWS.

Education

  • Marketing management (Mar, 2013–Apr, 2017) from BBA, B. ED

Fee details

    ₹1,000–2,000/hour (US$10.53–21.05/hour)

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