Question 1

Who is Karthik Rajesh Shet?

Accepted Answer

Karthik Rajesh Shet is an Applied AI Engineer and Founder based in Bengaluru, India, who builds production AI agents, MCP servers, agentic systems, SaaS platforms, and developer tools. He is the Founder & CEO of CodeMyFYP and the creator of Career-Agents — the open-source AI Career OS with 167+ specialized AI agents, a production MCP server, and a global CLI on NPM.

Question 2

What does Karthik Rajesh Shet specialize in?

Accepted Answer

Applied AI engineering: MCP (Model Context Protocol) server development, multi-turn tool-calling agents, RAG pipelines, agentic AI workflows, and LLM API integration (Claude, OpenAI, Gemini). Also specializes in backend engineering (Python, Flask, Node.js, TypeScript), full stack development (Next.js, React.js), AI watermarking & provenance (C2PA, SARIF), codebase RAG (AST parsing, pgvector), and multi-agent orchestration (LangChain, LangGraph, BullMQ).

Question 3

What company did Karthik Rajesh Shet found?

Accepted Answer

He founded CodeMyFYP IT & Software Solutions in 2025, where he built Cody (a production WhatsApp AI agent with multi-turn tool-calling), a custom MCP server for Career-Agents, and 15+ production-grade applications. He also founded CodeMyFYP Academy in 2026 — a multi-tenant EdTech SaaS platform officially listed on the AICTE National Internship Portal.

Question 4

What is Career Agents?

Accepted Answer

Career-Agents is Karthik's flagship open-source AI Career Operating System — 167+ specialized AI agents across 19 divisions, a Spoken Voice Lab (27 languages), ATS Resume Studio, FAANG Interview Tracks, GitHub Portfolio Auditor, Career Knowledge Graph, and a production MCP server (Claude Desktop, Cursor, Windsurf). Published as a global CLI on NPM (npm install -g career-agents). 39 GitHub stars, 7 forks.

Question 5

What is an MCP server and has Karthik built one?

Accepted Answer

Yes. MCP (Model Context Protocol) is an open standard for exposing tool definitions to LLM clients like Claude Desktop, Cursor, and Windsurf. Karthik built and maintains a production MCP server exposing 10 tools that power Career-Agents. He has also designed MCP integrations for ClaudeMark and NVIDIA Agent Doctor.

Question 6

What technologies is Karthik Rajesh Shet strongest in?

Accepted Answer

AI: Claude API, OpenAI API, Gemini API, MCP server development, multi-turn tool-calling, RAG pipelines (AST-parsed, pgvector), LangChain, LangGraph, prompt engineering. Backend: Python, Flask, Node.js, Express.js, Fastify, TypeScript. Frontend: Next.js (App Router), React.js. Databases: PostgreSQL, MongoDB, Redis, Prisma ORM. DevOps: Docker, GitHub Actions, AWS. Also Kotlin + Jetpack Compose for Android AI apps.

Question 7

Does Karthik Rajesh Shet have experience with AI agents and LLMs in production?

Accepted Answer

Yes — direct production experience: (1) Cody, a multi-turn tool-calling WhatsApp AI agent (Flask + Claude Haiku) handling real sales traffic; (2) a custom MCP server powering 167+ AI agents in Career-Agents; (3) ClaudeMark (AI watermark forensics, C2PA, SARIF); (4) CodeRAG (AST-parsed codebase RAG with pgvector); (5) GP Support Agent (LangChain + LangGraph RAG with evaluation harness); (6) NVIDIA Agent Doctor (GPU diagnostics + MCP). His portfolio site also runs a production RAG chatbot grounded in real vector-similarity search.

Question 8

What open-source projects has Karthik Rajesh Shet built?

Accepted Answer

Career-Agents (39 ⭐, 7 forks — AI Career OS + MCP server + NPM CLI), ClaudeMark (9 ⭐ — AI watermark forensics), TraceGraph AI (LLM trace graph diagnostics), aiskills (AI engineering skill library), NVIDIA Agent Doctor (GPU diagnostics CLI + MCP), CodeRAG (AST-parsed codebase RAG), Kestrel (autonomous software engineering + multi-agent orchestrator), LearnOS AI, CareerByte AI, AdIntel AI, GPU Insight AI, and more across 57+ repositories.

Question 9

Has Karthik Rajesh Shet led or mentored engineering teams?

Accepted Answer

Yes. He has led and mentored 40+ interns and junior developers across 10+ live Agile projects at CodeMyFYP, establishing sprint workflows, PR standards, code review processes, and structured technical onboarding.

Question 10

What are Karthik's competitive programming and CS fundamentals like?

Accepted Answer

Strong — 351+ LeetCode problems solved (104 Easy, 181 Medium, 66 Hard) with a 92.91% acceptance rate (Java: 232, Python3: 100). 6-Time Winner & 3-Time Runner-Up in Sadhana Coding Contests. 7,000+ GitHub contributions across 57+ repositories in the last year.

Question 11

What kind of roles is Karthik Rajesh Shet looking for?

Accepted Answer

Applied AI Engineer, AI Infrastructure Engineer, Agentic AI Engineer, MCP Server Developer, Senior Software Engineer, Founding Engineer, Full Stack AI Engineer, or AI Builder roles — particularly at companies building AI-native products, agentic systems, LLM-powered SaaS platforms, or developer tools.

Question 12

How can I contact Karthik Rajesh Shet?

Accepted Answer

Email kartikrshet@gmail.com, connect on LinkedIn at linkedin.com/in/karthik-rajesh-shet, view his code on GitHub at github.com/karthikrshet, or explore Career-Agents at npmjs.com/package/career-agents.

GitHub Intelligence Dashboard

Flagship: Career Agents

Karthik Rajesh Shet @karthikrshet