AI & ML EXPERTISE
GenAI & NLP

GENERATIVE AI & RAG

AWS BedrockAzure OpenAIHybrid RAG

Prompt Engineering & Structured Outputs

LangGraph

AGENTIC WORKFLOWS

Multi-AgentLangChainTool CallingMCP

Autonomous State Machines & Orchestration

Governance

EVALS & GUARDRAILS

Pydantic v2HITL GatesLLM Evals

Strict Schema Validation & Hallucination Defense

CORE PROCESSOR
MOHD HANNAN
CORE_V2.5

AI ENGINEER

SYS_ACTIVE

AI Engineer with 2+ years of enterprise experience building Generative AI, LangGraph multi-agent workflows, and cloud native architectures.

⚡ AGENTIC ORCHESTRATION
LINKEDINGITHUB
EXPLORE PROJECTS →
> sys.mount('Mohd Hannan') -> AI & Software Engineer initialized
STACK & CLOUD RACKBUS: 64-BIT
Web & APIs

FULL STACK DEVELOPMENT

Next.js 15React.jsFastAPINode.js

TypeScript, Python, Java & REST/GraphQL

Cloud Native

CLOUD & DEVOPS

AWSAzureDockerCI/CD

Microservices & Automated Deployments

Data Layer

DATABASES & VECTOR STORES

PostgreSQLpgvectorMongoDBMySQL

1536-D Vector Indices & Relational Schemas

SEC_02
OPERATOR BIOMETRICS
ID: MHS-01
Mohd Hannan
Mohd Hannan
AI ENGINEER
EXPERIENCE0+ YRS ENTERPRISE
CLEARANCESYS_ONLINE : LVL 5
02 // SPECIFICATION & ARCHITECTURAL OVERVIEW
REV 2.6.4

ArchitectingIntelligentSystems&CloudNativePlatforms

AI Engineer with 2+ years of experience building enterprise AI and full stack applications. Experienced in developing Generative AI and Agentic AI solutions with strong expertise in AWS, Azure, Microservices, and cloud native application development.

2+ years building enterprise-grade applications
Expert in Generative AI & Agentic AI solutions
Full Stack + Cloud Native Architecture
AWS, Azure & Microservices specialist

Agentic AI

LangGraph state machines & tool calling

Generative AI & RAG

AWS Bedrock & pgvector hybrid search

Cloud Native

Next.js, FastAPI & AWS microservices

FID_01 [SMT_ALIGN]
FID_02 [SMT_ALIGN]
FID_03 [GND_PLANE]
FID_04 [REF_CLOCK]

Technical Stack & Microchip Components

ALL BUSSES OPERATIONAL
IC_PKG: BGA-256

Languages

SLOT 01

Core programming languages

Python
Java
JavaScript
TypeScript
SQL
ARCH: LANG_CORE_V364-BIT DUAL
IC_PKG: QFP-128

Frameworks

SLOT 02

Web & API frameworks

React.js
Next.js
Node.js
Express.js
FastAPI
Redux
ARCH: FWRK_FASTAPI_NEXTASYNC_I/O
IC_PKG: BGA-512

Generative AI & NLP

SLOT 03

AI/ML & Natural Language Processing

LLMs
Generative AI
NLP
Prompt Engineering
Embeddings
Tool Calling
Structured Outputs
Hybrid Search
RAG
ARCH: NEURAL_TENSOR_RAG1536-D EMB
IC_PKG: BGA-512

Agentic AI & Orchestration

SLOT 04

AI Agent systems & workflows

LangGraph
LangChain
AI Agents
Multi Agent Workflows
Agent Harness
Evals
Guardrails
HITL
MCP
ARCH: AGENTIC_FSM_GRAPHSTATE_CH
IC_PKG: QFP-256

Cloud & DevOps

SLOT 05

Cloud platforms & deployment

AWS
Azure
Docker
CI/CD
GitHub Actions
Microservices
Azure OpenAI
AWS Bedrock
ARCH: CLOUD_MICROSERVICESMULTI_AZ
IC_PKG: BGA-384

Databases & Tools

SLOT 06

Data storage & management

PostgreSQL
MySQL
MongoDB
DynamoDB
Vector DB
ARCH: VECTOR_RELATIONAL_DBPCIE_GEN5
SEC_03
03 // PRODUCTION HARDWARE & CASE STUDIES

ArchitectedAISystems

Click any modular computing unit to open interactive neural data flow diagrams & technical telemetry.

UNIT 01

HyperCart AI — Autonomous Multi-Agent E-Commerce Operating System

Full-stack, enterprise-grade AI commerce platform featuring dynamic Text-to-SQL intent routing, structured product schema generation with Pydantic v2, pgvector RAG customer support, and human-governed safety guardrails.

Dynamic Text-to-SQL Routing: OmniAgent compiles parameterized read-only SQL with wildcard matching & fuzzy fallbacks
Structured Product Agent: Dynamic taxonomy injection + strict Pydantic v2 schema generation for full variant matrices
Next.js 14PythonFastAPILangChainPostgreSQLpgvectorPydantic v2Docker
EXPLORE ARCHITECTURE
UNIT 02

Proptech — Smart Property Assistant

AI-powered real estate assistant featuring a hybrid Text-to-SQL and RAG pipeline. Includes an LLM-based Intent Router, semantic guardrails, and a modern split-pane responsive UI for instant visual feedback.

Intelligent Query Routing: Zero-shot LLM classification distinguishing structured vs unstructured intent
Secure Text-to-SQL Agent: Dynamic parameterized SQL generation with strict read-only query guardrails
Next.js 15PythonFastAPILangChainPostgreSQLpgvectorDocker
EXPLORE ARCHITECTURE
UNIT 03

Infuse — Enterprise RAG Document Analyzer

Enterprise-grade Retrieval-Augmented Generation system for analyzing complex PDF documents with high accuracy and citation grounding.

Hierarchical PDF Ingestion: Drag-and-drop processing with layout and table preservation
Semantic Chunking & Embedding: Token-aware splitting with high-density vector embedding generation
Next.jsFastAPITypeScriptVector DBOpenAIDocker
EXPLORE ARCHITECTURE
SEC_04
04 // CAREER LOG & HARDWARE REGISTERS

ExecutionTrackRecord

2+ YEARS ACTIVE DEPLOYMENTS

AI Engineer

@ Stepping Cloud Consulting

2025 - PresentNew Delhi, India
Architected an advanced Retrieval-Augmented Generation (RAG) pipeline for an enterprise ticketing system, enabling seamless document ingestion and contextual Q&A utilizing Python, LangChain, Vector DBs, and Hybrid Search.
Engineered an automated email processing engine powered by AWS Bedrock to instantly summarize complex support threads and generate highly accurate draft responses via Prompt Engineering and Structured Outputs.
Architected a document-to-document RAG solution using Azure OpenAI and LangChain to parse massive text corpora, synthesize the retrieved context, and generate precise, structured output documents with enforced Guardrails to prevent hallucinations.
Developed core modules for a branded alumni portal designed to streamline employee exits, strengthen alumni connections, enable referrals, and provide personalized career opportunities through an integrated AI-based job recommendation system.
Built core platform modules using React.js, Node.js and deployed the application using AWS EC2, AWS S3, CloudFront and AWS RDS.
Designed and developed a complete HR Dashboard as a standalone full-stack solution, enabling HR to manage employees.
Built a complete DocuSign-based workflow using React.js, DynamoDB and Node.js to automate document signing, sending, tracking, and signature retrieval.
PythonJavaScript/TypeScriptReact.jsNode.jsFastAPIAWSLangGraphDockerAzure OpenAIAWS BedrockAWS S3AWS EC2AWS RDSAWS CloudFrontAWS DynamoDB
SEC_05
05 // TRANSCEIVER & DIRECT INTERFACE
PORT: 443 / SSL

ReadytoTransmit?

Open to enterprise AI engineering opportunities, LangGraph agent architectures, and full-stack cloud collaborations.

mohdhannan774@gmail.com
INITIATE TRANSMISSION