Vibe Coder / Senior AI Developer at Accellor / IIT Mandi

I turn fuzzy product ideas into shipped AI systems:
live apps, agent workflows, data products, and the glue code that makes them useful.

Currently Senior AI Developer at Accellor, building RAG systems, multi-agent workflows, AI agents, and generative AI products.

Current focus: RAG + Multi-Agent + MCPs Mode: Product-minded AI Writing: Claude Code Field Guide

About

I build AI systems that turn messy product intent into useful workflows: RAG products, multi-agent automations, analytics surfaces, and the glue code that helps teams ship faster.

I am currently a Senior AI Developer at Accellor, with prior data science work across RevSure AI, Pixis, and LEAD School.

Projects

development / personal

Raj Agent OS Portfolio

Agent OS style portfolio and writing platform for AI engineering work, Claude Code field notes, live system previews, and privacy-first engagement logging.

  • Vite
  • React
  • TypeScript
  • Agent OS
  • Portfolio

beta / personal

Minimalist Plain Text Portfolio

Minimalist plain-text version of the portfolio for rajsharma.space with fast reading, direct links, resume, writing, and project summaries.

  • Flask
  • HTML
  • CSS
  • Plain Text
  • Portfolio

beta / personal

Sparkpad

Markdown-first text workspace with diagram + math rendering.

  • Markdown
  • Mermaid
  • KaTeX
  • JavaScript

development / personal

SplitKar Platform

Expense splitting + collaboration product built as a multi-repo system (core + UI + chat).

  • TypeScript
  • UI
  • Product
  • Vercel

initial / personal

ZenConnect (SplitKar Chat)

Chat + collaboration surface paired with SplitKar.

  • TypeScript
  • Chat
  • UI

initial / personal

Sheetwise Expense Buddy

Utility app for streamlined expense workflows and summaries.

  • Expense
  • UI
  • Vercel

development / personal

ActionHub Website

Marketing + documentation site for ActionHub with SEO-focused updates.

  • Next.js
  • TypeScript
  • SEO
  • Landing

beta / personal

Timer / Clock / Stopwatch

Real-time timekeeping utility app shipped end-to-end.

  • TypeScript
  • Utility
  • Vercel

beta / personal

Invitation / Lifestyle Sites

A set of minimal single-purpose sites demonstrating rapid shipping: invitations, plans, and quick static pages.

  • HTML
  • Static
  • Vercel

initial / personal

Agentic Data Analysis

Exploration into agent-like analytical workflows combining reasoning with structured data steps.

  • Python
  • LLM
  • Agents
  • Data Analysis

initial / personal

Recommendation System

Classic recommendation modelling foundations for personalization use cases.

  • Python
  • ML
  • Recommendation

development / corporate

Corporate Projects (private)

Reserved entries for corporate work. Company name + timeline will be added once confirmed.

  • Confidential
  • Production AI
  • Data Systems

Experience

Present

Senior AI Developer, Accellor

India / Hybrid / Remote

  • RAG
  • Multi-agent systems
  • Workflows
  • AI agents
  • Generative AI

Current AI systems work: Current role, project details coming later.

2025-09 - 2026-02 · 6 mos

Data Scientist, RevSure AI

Bengaluru, Karnataka, India / Hybrid

  • Predictive Modeling
  • Generative AI
  • Lead Fit Scoring
  • Lead Propensity
  • Title Standardization
  • HMM (Hidden Markov Models)
  • Marketing Attribution
  • Data Standardization
  • LLM + Rules
  • Feature Engineering

Lead Fit scoring system: Prioritized accounts using firmographic, behavioral, and conversion signals to improve sales targeting efficiency.

Lead Propensity model: Predicted progression across the funnel (MQL→SQL→Opportunity→Closed-Won) to improve forecasting and campaign optimization.

Title Standardization: LLM + rule-based cleaning/normalization for CRM job title data to improve downstream model performance and reporting.

Probabilistic multi-touch attribution: HMM-based attribution to quantify channel impact and move beyond static rule-based attribution.

Buying Stage inference: Combined product, marketing, and sales signals to infer customer journey stages and provide real-time visibility.

LLM-based data standardization: Applied LLM-based semantic normalization techniques to reduce manual effort and improve data quality across pipelines.

2023-04 - 2025-07 · 2 yrs 4 mos

Data Scientist, Pixis

Bengaluru, Karnataka, India / Hybrid

  • Generative AI
  • Predictive Modeling
  • Campaign Optimization
  • AWS S3
  • AWS Athena
  • Feature Engineering
  • Data Pipelines
  • Production ML Integrations

Predictive targeting & optimization models: Behavioral, engagement, and contextual signal models to improve campaign performance.

Marketing data pipelines: Built real-time + batch processing pipelines using AWS S3 + Athena for ML inference and reporting.

Feature engineering framework: Reusable feature creation workflow to transform raw signals into ML-ready inputs.

Codeless AI infrastructure: Enabled non-technical users to leverage ML insights in workflows.

Early generative AI experiments: Prompt-based experimentation and integrations for targeting/segmentation automation.

2021-09 - 2022-05 · 9 mos

Product Analyst I, LEAD School

Bengaluru, Karnataka, India

  • Product Analytics
  • Data Analysis
  • Tableau
  • Looker
  • Kibana
  • Python
  • Apache Airflow

Product dashboards & reporting: Built interactive dashboards to track performance and business metrics for product teams.

Reporting pipeline automation: Automated reporting workflows using Python + Airflow, reducing manual reporting effort.

2019-05 - 2021-06 · 2 yrs 2 mos

Student Representative, Career and Placement Cell, IIT Mandi

IIT Mandi

Placement policy & stakeholder communication: Improved student placement experience and policy execution through coordination with academic departments and administration.

2019-12 - 2020-01 · 2 mos

Intern, Geo Carte Radar Technology Pvt. Ltd.

Gandhinagar, Gujarat, India

  • Data Interpretation
  • AutoCAD
  • ArcGIS
  • POC Development

Crack detection POCs: Led POCs and problem-solving for crack detection using tooling and data interpretation.

Data quality & troubleshooting: Troubleshot technical issues to ensure accurate submissions and data integrity for contractors.

Skills

Core Skills

  • Agentic Product Engineering
  • RAG Systems
  • Multi-agent Workflows
  • AI Agents
  • Generative AI
  • LLM Evaluation
  • Machine Learning
  • Data Product Thinking

Tech Skills

  • Python
  • TypeScript
  • React
  • SQL
  • PostgreSQL
  • Vector Databases
  • Airflow
  • AWS
  • Google Cloud Platform
  • Analytics & Experimentation

Writing

Part 1 / 8 min read

Claude Code for Beginners: 10 Habits That Change Everything

Ten habits that make Claude Code feel less random and more like a useful coding partner.

Read plain-text version

Part 2 / 9 min read

Claude Code Advanced Workflow: The Full Stack

A full-stack workflow for planning, model choice, memory, review, hooks, skills, and parallel execution.

Read plain-text version

Part 3 / 8 min read

Hooks: Give Claude Code Guard Rails That Actually Run

How to turn repeated reminders into Claude Code hooks that actually run.

Read plain-text version

Part 4 / 7 min read

Skills: Repeatable Process On Demand

Why reusable skills beat ad-hoc prompts for engineering workflows that need process.

Read plain-text version

Part 5 / 10 min read

Slash Commands: The Power Shortcuts Most Developers Overlook

A practical map of the slash commands worth building into Claude Code muscle memory.

Read plain-text version

Part 6 / 8 min read

Plan Mode: Think Before You Code

How plan mode separates deciding what should change from writing the code.

Read plain-text version

Part 7 / 8 min read

Commands vs Skills: Know the Difference, Use Both Right

A modern decision rule for choosing between prompt-like commands and structured skills.

Read plain-text version

Resume

Formal wording: Senior AI Developer at Accellor, Data Scientist at RevSure AI and Pixis, Product Analyst I at LEAD School.

Life

Early years - Mar 2009

Early years with my maternal grandparents

Childhood / Chauri

The first chapter was rooted in Chauri, around my maternal grandparents' home. It gave me a grounded start: family, discipline, and the kind of curiosity that comes from watching people solve everyday problems with limited resources.

  • Grew up close to family and village life
  • Built early curiosity through observation
  • Carried a grounded sense of effort into school

Mar 2009 - Mar 2011

Village-school foundation through Class 2

Primary / Kanhaiyachak

Primary schooling started in my village, Kanhaiyachak. It was a simple beginning, but it built the first habits of showing up, learning steadily, and staying close to the realities around me.

  • Early schooling through Class 2
  • Village-first learning environment
  • Built consistency before moving to Jehanabad

Classes 3-6

Middle-school years at Shanti Kunj Public School

Schooling / Jehanabad

At Shanti Kunj Public School, the academic world widened. This was where school became more structured and I started building confidence across subjects.

  • Moved from village schooling into Jehanabad
  • Built stronger academic rhythm
  • Continued developing interest in science and problem solving

Classes 7-10

Maths and physics foundation at Bal Vidya Niketan

Schooling / Jehanabad

Bal Vidya Niketan became the phase where maths and physics started standing out. The focus shifted from just doing well in class to preparing for a larger academic path.

  • Strengthened mathematics and physics
  • Built exam discipline and competitive intent
  • Prepared the base for science and JEE preparation

Mar 2015 - Apr 2017

Science and JEE preparation at Abhayanand Super 30

Higher Secondary / Patna

The Super 30 phase in Patna sharpened everything: science, JEE preparation, independence, and the belief that a student from a small-town background could compete at a national level.

  • Studied science with a strong maths and physics focus
  • Prepared intensively for JEE
  • Built resilience, discipline, and independent thinking

Aug 2017 - May 2021

B.Tech in Civil Engineering with a management minor

IIT Mandi / Indian Institute of Technology Mandi

IIT Mandi gave me a technical foundation through Civil Engineering, plus a management minor and a wider world of projects, leadership, and problem-solving. It was also the bridge from academic strength into product and data thinking.

  • B.Tech in Civil Engineering with a minor in Management
  • Built technical, analytical, and leadership foundations
  • Represented IIT Mandi in technical competitions and campus initiatives

2021 - Present

From analytics and data science to agentic AI engineering

Professional Journey / LEAD School, Pixis, RevSure AI, Accellor

The professional chapter started with product analytics, moved into production data science and revenue intelligence, and now sits in agentic AI systems: RAG, multi-agent workflows, AI agents, and generative AI products.

  • Product analytics and reporting automation at LEAD School
  • Production ML, campaign optimization, and data systems at Pixis and RevSure AI
  • Current focus: agentic AI systems and multi-agent workflows at Accellor

Contact

Preferred channel: contact@rajsharma.space.