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Abhishek Yadav // Product Engineering
Open to AI Engineer Roles · Remote / India
Hi, I'mAbhishek

Building production AI systems — RAG pipelines, agentic workflows & LLM-powered apps. Live on HuggingFace.

RAGAgentic AIMCPClaude APILangGraphChromaDB
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Internships
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Anthropic Certs
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Live AI Projects
26.4499°N · 80.3319°E · KANPUR
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// 01 — About Me

Building AI that
actually ships.

I'm Abhishek Yadav — BCA (2022–2025, CGPA 7.59) from CSJMU Kanpur, positioning as an AI Engineer. I don't just study AI — I deploy it.

My flagship: 3-stage RAG + Computer Vision + Agentic AI pipeline on HuggingFace, powered by Anthropic Claude API. Plus an MCP-powered Lead Gen System with LangGraph — architecturally rare among Indian fresher profiles.

6 internships. 11 Anthropic Academy certs. Targeting AI Engineer / LLM Engineer / GenAI Developer — remote-first or Bengaluru / Hyderabad / Noida.

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PROJECTS
// 02 — Production AI Systems
Agentic AI · RAG PipelineLIVE

AI Document Intelligence

Problem: Enterprises drown in unstructured documents — PDFs and scanned files sit in silos, completely inaccessible to semantic search or intelligent querying.

Solution: Built a 3-stage pipeline: Computer Vision for document parsing → RAG with ChromaDB + all-MiniLM-L6-v2 → Agentic AI layer via Anthropic Claude API for intelligent Q&A and summarisation.

Key Highlights

  • Live deployed on HuggingFace Spaces
  • 3-stage RAG + CV + Agentic pipeline
  • Semantic search via ChromaDB embeddings

Core Tech

PythonAnthropic APIChromaDBall-MiniLM-L6-v2FastAPI
RAG + CV + AGENTIC_AI
Multi-Agent · MCP Architecture

MCP-Powered Lead Generation

Problem: Sales teams waste hours manually scraping, qualifying, and enriching leads with no intelligent orchestration layer.

Solution: Multi-agent system using the Model Context Protocol (MCP) with LangGraph orchestration. Agents autonomously scrape, enrich, qualify, and score leads using Anthropic Claude as the reasoning backbone.

Key Highlights

  • Multi-agent MCP architecture
  • LangGraph stateful workflow orchestration
  • Anthropic Claude tool-use reasoning

Core Tech

PythonMCPLangGraphAnthropic APIFastAPI
Source
MULTI_AGENT_ORCHESTRATION
// 03 — AI System Architecture

Production-Grade
AI Pipeline Design.

Inspired by LlamaIndex data pipelines and LangChain agent orchestration patterns — these are the actual architectures powering my live projects.

LlamaIndex-Inspired
RAG data pipeline · contextual retrieval · vector indexing
LangChain-Inspired
Agent orchestration · tool-use · multi-step reasoning chains
Anthropic MCP
Model Context Protocol · structured tool calls · Claude API
Project 1 — AI Document Intelligence
// SYSTEM ARCHITECTURE · LlamaIndex-Inspired
RAG + Agentic AI Pipeline
MESSAGE BUS ACTIVE
L1: INGRESS
Document Loader
PDF · Image · Web
ACTIVE
L2: EMBEDDING
Vector Embedding
all-MiniLM-L6-v2
ACTIVE
L3: RETRIEVAL
Vector Store
ChromaDB · Search
ACTIVE
L4: REASONING
Claude API
Agentic · Tool Use
ACTIVE
L5: OUTPUT
Response
Q&A · Summary
ACTIVE
System Load: Stable
Encryption: Active
Throughput: 4.2k/min
p99 LATENCY: 28ms
Project 2 — MCP Lead Generation System
// MCP ORCHESTRATION · LangChain-Inspired
Multi-Agent Lead Pipeline
LangGraph · MCP
Claude API
ORCHESTRATOR
Scraper Agent
Web data extraction
tool_call
Enrich Agent
CRM enrichment
tool_call
Score Agent
Lead qualification
tool_call
Outreach Agent
Personalised copy
tool_call
DiscoveryEnrichmentQualificationOutreach DraftCRM Update
// 04 — Technical Arsenal

AI / LLM Stack

Core Strength · Actively Deploying in Production

PRIMARY EXPERTISE
Anthropic Claude APIRAG ArchitectureMCP (Model Context Protocol)LangGraphLangChainChromaDBall-MiniLM-L6-v2HuggingFace SpacesAgentic AI PatternsPrompt EngineeringVector DatabasesContextual RetrievalOpenAI APIPyTorch

Languages

PythonJavaScriptTypeScriptJavaC++

Frontend & Backend

React.jsNext.jsFastAPINode.jsExpress.jsTailwind CSSDjangoWebSockets

Data & Infrastructure

MongoDBPostgreSQLMySQLRedisDockerRailwayGit / GitHubAWS (Basic)
// 05 — Experience & Certifications

6 Internships.
Real World Impact.

Security research → full-stack dev → AI engineering. Each role built the stack.

Google Developer Campus

Developer Program Participant

2024

AI / ML track — build & deploy workshops

Codevirus Security

Security & Development Intern

2024

Vulnerability assessment & secure code review

Code-A-Nova

Full Stack Developer Intern

2023

React + Node.js production feature delivery

Klynt Solutions

Software Developer Intern

2023

Client-facing web application development

HexSoftwares

Web Developer Intern

2023

Frontend engineering & UI component systems

Self-Directed AI Research

Independent Builder

2022–25

RAG systems, agentic AI, MCP architecture

11 Anthropic
Certifications.

Full Anthropic ecosystem — Claude API, MCP, Agentic AI, RAG & beyond.

Anthropic API Fundamentals
Anthropic Academy · 2024
CORE
MCP & Tool Use Mastery
Anthropic Academy · 2024
ADVANCED
Agentic Design Patterns
Anthropic Academy · 2024
ADVANCED
Prompt Engineering
Anthropic Academy · 2024
CORE
Claude Code & Workflows
Anthropic Academy · 2024
TOOLS
RAG Architecture
Anthropic Academy · 2024
SYSTEMS
Files API & Prompt Caching
Anthropic Academy · 2024
OPTIMISE
Extended Thinking
Anthropic Academy · 2024
ADVANCED
Batch Processing
Anthropic Academy · 2024
SCALE
AI Fluency 4D Framework
Anthropic Academy · 2024
STRATEGY
Multi-Agent Orchestration
Anthropic Academy · 2024
ADVANCED
Verified by Anthropic Academy
11 certs · Extremely rare among Indian fresher profiles
// 06 — Let's Build Together

OPEN TO
AI ROLES.

Looking for AI Engineer / LLM Engineer / GenAI Developer roles. Remote-first or Bengaluru / Hyderabad / Noida. Fresh grad with live deployments & 11 Anthropic certs.

Get in Touch