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Mitul Bhatia
About / Experience and approachMITULBHATIA.DEV
[CANDIDATE DOSSIER]REF: MB-2026-AI
COORDINATES: 28.99° N, 77.02° E
SONIPAT, HARYANA · INDIA
SEAL // 2026
MB
Mitul Bhatia
AI / Full-Stack Engineer
ACADEMIC CGPA
9.65 / 10.0
INSTITUTION
Newton School of Tech
STATUS: RESEARCH & INDUSTRYVERIFIED RECORD
Focus Area
Agentic Systems & LLM Infra
Current
Kolably (Intern)

Engineer, student, and careful system builder.

I am an AI and full-stack engineering student at Newton School of Technology, Rishihood University. My work spans agent orchestration, retrieval systems, backend APIs, and real-time product experiences.

I care about the parts that make an AI system dependable: clear state, useful guardrails, grounded retrieval, and software that remains understandable after the demo.

Backend and AI systems engineer with startup experience at Kolably and Raindeer.social, hands-on work across multi-agent systems, RAG pipelines, FastAPI, React, and real-time infrastructure, holding a 9.65 CGPA at Newton School of Technology.

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Track Record // Industry & Research

Industry experience & engineering roles

Hands-on software development at high-velocity startups, from autonomous multi-agent systems to backend APIs and GPU compute cohorts.

[3 Documented Appointments]
EXP-01
Jul 2026 - Sep 2026
Remote · Creator-business collaboration platform

Software Developer Intern

Kolably
FastAPINode.jsREST APIsPostgreSQLAuth
  • Worked alongside the founding team on a live platform connecting local businesses with nearby content creators.
  • Contributed backend APIs, product features, and bug fixes while following the team's security and confidentiality practices.
EXP-02
Jun 2026 · 1 month
Remote · AI-agent social media platform

AI Agents Lead

Raindeer.social
CrewAILangGraphPythonMulti-AgentAsyncio
  • Led the AI layer of a 10-agent orchestration system built with CrewAI and LangGraph.
  • Contributed orchestration and pipeline logic across research, content generation, design, and scheduling.
EXP-03
2025 - 2026
Selected cohort · Dedicated GPU compute

AI Studio Fellow

Newton School of Technology
PyTorchNVIDIA GPUsFAISS RAGLangChain
  • Prototyped and shipped production-oriented agentic and RAG pipelines through coursework and independent systems.

How I approach the work

  1. 01

    Start with the user path

    Define the decision or task before choosing models, tools, or infrastructure.

  2. 02

    Make state explicit

    Keep orchestration steps, memory boundaries, and failure handling visible in the system design.

  3. 03

    Measure the critical path

    Track latency, matching quality, and retrieval behavior where they affect the product experience.

  4. 04

    Ship and iterate

    Move from prototype to a working interface, then use real constraints and feedback to improve it.

Education

B.Tech in Artificial Intelligence

Newton School of Technology, Rishihood University · 2024 - 2028

9.65 / 10.0 CGPA · Through Semester 4 · Currently in Semester 5

Selected for the competitive AI Studio cohort with dedicated GPU compute for agentic and RAG projects.

Other signals

LeetCode
1400+
Codeforces
900+
Tata Data Visualisation
Forage Job Simulation · Jan 2026
Hacktoberfest Contributor
Reviewed open-source pull requests
Mumbai Hacks
Prototype and presentation participant