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ManisCodeBase/README.md

Manikanta Neerukattu

Applied AI Engineer | Agentic AI & RAG Systems | Full-Stack (.NET + React) | Cloud AI Architect

9+ years engineering experience • AI-first systems • ERP, CRM, HCM, Healthcare & Finance • Azure & AWS


🧠 Professional Summary

I am a Senior Software Engineer turned Applied AI Engineer, focused on building production-grade AI systems — not demos.

  • 🧩 Agentic AI systems with tool-calling, planning, memory, and orchestration
  • 📚 Enterprise-scale RAG pipelines across structured & unstructured data
  • 🏥 Deep experience in Healthcare (EMR, compliance) and Financial systems
  • ☁️ Strong in Azure AI Foundry, AWS Bedrock, and hybrid cloud deployments
  • 🏗️ Engineering mindset: scalability, observability, security, and governance

My work bridges LLMs, classical engineering, cloud platforms, and regulated industries.


🤖 AI / GenAI Stack (Vendor-Neutral)

Foundation Models

  • OpenAI (GPT)
  • Anthropic (Claude)
  • Mistral
  • Meta LLaMA
  • Azure OpenAI
  • AWS Bedrock Models

Agent & Orchestration Frameworks

  • LangChain
  • LangGraph
  • OpenAI Agents SDK
  • Microsoft AutoGen
  • CrewAI

Agentic Patterns

  • Tool-calling & function routing
  • Planner-Executor agents
  • Multi-agent collaboration
  • Memory-augmented agents
  • Human-in-the-loop workflows

📚 RAG & Knowledge Systems (Advanced)

  • Agentic RAG (query planning + retrieval + synthesis)
  • Hybrid search (BM25 + vector)
  • Metadata-aware chunking
  • Re-ranking & grounding
  • Evaluation & hallucination control
  • Structured + unstructured fusion (PDF, XBRL, SQL, APIs)

Vector Databases

  • ChromaDB
  • FAISS
  • Pinecone
  • Azure AI Search (Vector)
  • PostgreSQL (pgvector)

🔌 MCP & Tool Integration (2025 Trend)

  • Model Context Protocol (MCP)
  • Tool registry & dynamic tool discovery
  • Secure tool execution boundaries
  • Enterprise system integration:
    • Databases
    • REST APIs
    • Cloud services
    • Internal business tools

🖥️ AI Frontend & UX

  • Streamlit (AI dashboards & copilots)
  • React-based AI UIs
  • Prompt-driven workflows
  • Human-AI interaction design
  • Observability-friendly UI patterns

☁️ Cloud AI Platforms

Azure

  • Azure AI Foundry
  • Azure OpenAI
  • Azure Functions
  • Databricks
  • Synapse Analytics
  • Fabric
  • Azure DevOps CI/CD

AWS

  • AWS Bedrock
  • S3, Lambda
  • Cloud-native AI workloads

🧰 Core Engineering Stack

Backend

  • C#, .NET 6/8, ASP.NET Core
  • Python (FastAPI, PySpark)
  • Microservices & APIs

Frontend

  • React (18+)
  • Angular
  • TypeScript

Data

  • SQL Server, PostgreSQL
  • Snowflake
  • Databricks
  • Data Lakehouse architectures

🏥 Industry Experience

Healthcare

  • EMR & patient communication platforms
  • Secure, compliant systems (EU & AU)
  • AI-assisted clinical documentation & workflows

Finance & Compliance

  • Regulatory disclosure platforms
  • AI-powered document intelligence
  • XBRL / iXBRL / financial data pipelines

🎓 Education & Research

  • PG Degree in Artificial Intelligence
    IIIT BangaloreCGPA: 3.85 / 4.0

  • Master’s Degree (Research-Oriented, Pursuing)
    Liverpool John Moores University, UK

  • Continuous research focus on:

    • LLM evaluation
    • Agentic reasoning
    • Retrieval optimization

🧪 Active & Upcoming Projects

  • 🔹 Enterprise-Grade Agentic RAG Platform
  • 🔹 MCP-Driven Tool-Integrated AI System
  • 🔹 Healthcare AI Knowledge Copilot
  • 🔹 Multi-Agent Compliance Intelligence System

(Repositories actively evolving)


🎯 Roles of Interest

  • Applied AI Engineer
  • Senior LLM Engineer
  • Agentic AI Engineer
  • AI Platform / Solutions Architect
  • AI Engineer (Healthcare / Enterprise)

📬 Let’s Connect

⭐ I build AI systems that survive production, scale in enterprises, and earn trust.

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