~/samarpit-nagpal GURUGRAM — 00:00

$ status — open to opportunities · Generative AI Engineer · Full-Stack · Gurugram, IN

Samarpit Nagpal

Generative AI Engineer & Full-Stack Developer shipping production-grade systems — LLM pipelines & AI agents, typed APIs, real-time platforms, and interfaces people actually enjoy using. Designed, built, and maintained end-to-end.

$ ls ./work — 10 projects

Selected Work

Wishmaker

AI Greeting-Card App · Backend & Admin Panel · Mediology

The backend and admin panel behind a consumer app on Google Play and the App Store: every greeting card is composed by a multi-model AI pipeline — text, image, and vision models orchestrated as async jobs, with per-image cost tracking, daily caps, and a batch mode that halves inference spend — plus end-to-end subscription billing driven by store webhooks.

$ react / node / postgresql / gemini · openai · openrouter / job queue / store webhooks / cron

multi-model pipelineasync orchestrationcost guardrails
2026

PDF Article Detection — Desktop App

On-Device AI · Windows & macOS · Mediology

A desktop app for Windows and macOS that publishers run on their own machines: they drop PDFs into a folder, a local AI model detects the articles on every page, and the app sends their coordinates to our platform over an API. Developed both the detection model and the desktop app. Live at multiple publishers, processing 200+ PDFs a day.

$ desktop app / on-device inference / computer vision / layout detection / rest apis

on-device ailayout detection200+ pdfs / day
2026

Ad Traffic Fraud Detection

Invalid-Traffic Platform · Mediology · Internal

Fraud-detection platform reconciling Google Ad Manager and GA4 signals across 350+ publisher domains and ~100M ad impressions — scoring every domain's risk, then vetting suspects with a Playwright crawler fleet and AI research agents before revenue is on the line.

$ react / node / google ad manager · ga4 apis / playwright / gemini

risk scoringai research agentscrawler fleet
2026

RAG Support Assistant

Retrieval-Augmented Generation · Self-Hosted LLM

A support and suggestion assistant that grounds a self-hosted LLM in an internal knowledge base. Documents are chunked and embedded with Sentence-Transformers, the top-k most relevant chunks are retrieved from ChromaDB for each query, and context-only prompting keeps answers grounded, with every answer citing the source chunks behind it.

$ python / sentence-transformers / chromadb / ollama / semantic search

ragvector searchhallucination control

Self-Hosted LLM Content Generator

Quizzes · Summaries · Podcasts · Open-Source LLM

An open-source LLM running on local infrastructure, with no external API calls, that turns source content into quizzes, summaries, and podcast scripts, plus a text-to-speech step that renders the scripts as podcast audio. Data stays private and inference costs stay low.

$ python / hugging face transformers / text-to-speech / local inference

self-hosted llmtext-to-speechprivate by design

Dynamic Config — SORTD

Publisher Config Middleware · Mediology

Config middleware inside SORTD, Mediology's publisher platform: publishers tune app behaviour from a UI — with an AI assistant that makes the changes for them and a live preview against the app — and updates propagate to production on the fly. No release cycle, no developer round-trip.

$ react / node / rest apis / ai assistant / live preview / on-the-fly config delivery

ai assistantzero-release updateslive preview
2026

Interview Drive

Walk-In Hiring & Assessment Platform · Mediology

The platform behind Mediology's walk-in interview drives. Candidates scan a QR code at the office, fill in their details, and take an assessment with randomised questions from a bank HR manages by difficulty. HR reviews the scores, assigns candidates to second-round interviewers, and reviews their feedback and shortlists. Two React apps (candidate and HR panel) and an Express server; 200+ candidates assessed.

$ react / express / node / qr check-in / randomised assessments / interviewer workflow

200+ candidatesqr check-inhr panel
2026

Bluestar PCM

IoT Monitoring Platform · IOTFY

Real-time monitoring for 3,000+ deployed IoT devices. Live fault detection and daily monitoring workflows that cut support response times for multiple internal teams.

$ typescript / mqtt / websockets / rest apis / real-time telemetry

2025

Zeno — Factory PMS

Production Management · IOTFY

End-to-end production management across 6+ factory stages — kit planning, SMT, assembly, testing — with OK/NG/rework flows tracking every manufactured device, gated by role-specific backend APIs for 10+ roles.

$ typescript / node / postgresql / rbac / workflow engine

2025

Online Library Platform

Full-Stack · Personal Build · Live

eBook marketplace with an integrated EPUB reader — highlights, notes, themes, progress tracking — plus author publishing, JWT auth with email verification, and Stripe checkout across 30+ REST endpoints.

$ react 18 / typescript / redux-toolkit / node / express / mongodb / stripe / epubjs

$ whoami

About Me

I like software you can lean on — the kind teams run their day on, and now the kind where agents do the heavy lifting.

I'm Samarpit — a software engineer in Gurugram, currently at Mediology Software, building AI-agent systems end-to-end: a consumer app whose greeting cards are composed by a multi-model pipeline, research agents that hunt ad fraud across hundreds of publisher domains, and the job queues, cost guardrails, and billing webhooks that keep it all shippable.

Before that, at IOTFY, I built the unglamorous, high-stakes middle of connected products: monitoring platforms watching 3,000+ devices in the field, factory floors tracking every unit from kit to test, and real-time pipelines that shaved ~80% off critical service operations.

My happy place is the full stack — a typed API on one end, an interface people actually enjoy on the other, and a database schema in between that won't embarrass me in a year. Lately that stack includes a model layer too: picking the right model for the job, keeping latency and spend honest, and designing for the runs that fail.

Off the clock: grinding data structures & algorithms, studying system design, and playing chess — where, much like in production, the losing move is always the one you didn't think through.

  • CurrentlySoftware Engineer @ Mediology Software
  • PreviouslySoftware Developer @ IOTFY
  • FocusGenerative AI & LLM systems · Full-stack product engineering
  • EducationMCA, Chandigarh University (ongoing) · BCA, IGNOU
  • Based inGurugram / Delhi NCR, India
  • ElsewhereChess boards & LeetCode
$ cat ./toolbox
Languages
javascript es6+ / typescript / python / sql
AI & Agents
openai · anthropic claude · gemini apis / langchain · langgraph / agent orchestration / multi-agent workflows / tool calling · function calling / mcp (model context protocol) / rag · vector embeddings (pgvector · pinecone) / semantic search / evals · llm-as-a-judge · langsmith / prompt & cost engineering
Frontend
react / next.js / redux / react query / tailwind css / vite
Backend
node.js / express / electron / mqtt / websockets / payment webhooks / jwt · rbac
Data
mongodb / postgresql / mysql / supabase / redis
Cloud & Ops
aws lambda / s3 / ec2 / docker / playwright automation / linux / ci-cd

$ mailto — have a role, a product, or a stubborn bug?

Let's build ↗

Usually reply within a day. Happy to walk through code, architecture decisions, agent pipelines, or why that one query was slow.