Generative AI Engineer with less than a year in Multi-Agent AI Systems & RAG Architectures
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Generative AI Engineer with half year of internships and personal projects experience in developing intelligent and agentic AI systems using CrewAI, AgnoAI, LangGraph, and AutoGen. Skilled in RAG architectures, LangChain, LangSmith, NLP, and multimodal AI with PyTorch. Experienced in building AI-driven solutions such as emotion detection, neural style transfer, and text summarization, with a focus on creating scalable, autonomous, and next-generation applications.
Bareilly College Bareilly - MJPRU
BCA
August 1, 2023 – June 30, 2026
Jai Narayan SV MI College
12th Std
June 1, 2021 – May 31, 2022
Codec Technologies India
Artificial Intelligence Intern
November 1, 2025 – February 1, 2026
Mumbai, Maharashtra, India
Euron Pvt. Ltd.
Generative AI Engineer Intern
October 1, 2025 – November 1, 2025
Bengaluru, Karnataka, India
NPC Dialogue Engine
June 1, 2025 – June 1, 2026
Designed and implemented an AI-powered NPC Dialogue Engine to drive immersive, believable interactive storytelling through characters with distinct, persistent traits. Leveraged the Gemini API and advanced Prompt Engineering to define and power multiple AI agents, each possessing a unique personality and behavioral profile. Engineered a robust state management system to facilitate long-term conversational memory and enable dynamic changes in NPC mood based on simulated in-game events. Developed an interactive, real-time control panel using Streamlit to manage character parameters, observe conversational flow, and tune the engine's behavior.
Admit-AI Nexus
June 1, 2025 – June 1, 2026
Automate admission analysis, student outreach, and decision workflows using secure, multi-agent AI systems. React (Vite) + FastAPI + Supabase backend orchestrating CrewAI, Agno agents, RAG pipelines, and LLMs via API-driven, containerized services. Multi-agent reasoning, secure vector-based retrieval, automated campaigns, batch CSV processing, and real-time analytics. Guardrails, access-controlled RAG, observability (logs, traces, latency), fallback routing, and DSA-based ranking & retrieval. Delivered a production-grade, auditable AI platform that replaces manual admission workflows with reliable, scalable, agent-driven intelligence.
AI Judicial Assistant Crew
June 1, 2025 – June 1, 2026
Developed an autonomous Multi-Agent Legal Analysis Crew to automate the time-intensive, initial stages of case research for the Indian judiciary, directly addressing the national case backlog. Orchestrated a four-specialized-agent system using CrewAI and Google Gemini, featuring dedicated Case Intake, Constitutional RAG, Precedent Search, and Synthesis agents. Implemented a LangChain RAG pipeline with ChromaDB on the Indian Constitution to ground the analysis in factual, up-to-date legal knowledge and retrieve relevant articles. Significantly augmented legal efficiency, reducing the time for high-level judicial summary generation from multi-hour manual review to minutes, delivered via an interactive Streamlit UI.
Agentic Data Scientist Crew
June 1, 2025 – June 1, 2026
Created an autonomous Multi-Agent Data Science Crew to streamline and fully automate the end-to-end data analysis workflow, from raw data ingestion to final human-readable reporting. Orchestrated a collaborative four-agent system using CrewAI and Google Gemini, integrating specialized Data Fetcher, Cleaner, Visualizer, and Report Agents. Engineered agents to handle complex data science functions, including missing value imputation, data tidying, exploratory data visualization, and comprehensive report drafting. Developed a powerful Proof-of-Concept for Agentic AI that demonstrates significant potential for automating foundational analytical work.
Open Agent Orchestrator (OAO)
June 1, 2025 – June 1, 2026
Designed a deterministic execution runtime to solve the "Orchestration Tax" in multi-agent systems, reducing execution overhead and enforcing strict governance policies. Built a parallel DAG scheduler, 5-state lifecycle engine (INIT → PLAN → EXECUTE → REVIEW → TERMINATE), and policy adapter compatible with LangChain and CrewAI. Achieved sub-linear overhead scaling (7.15x at n=8 agents vs 8x baseline). Published the core runtime as an open-source Python package on PyPI (open-agent-orchestrator).
View ProjectAI & Quantum Computing - Zero to Expert Bootcamp
Quantum Computing
June 1, 2026 – Present
open-agent-orchestrator
PyPI
June 1, 2026 – Present
RAG and Agentic AI
IBM
June 1, 2026 – Present
AI Engineering
IBM
June 1, 2026 – Present
Introduction to Quantum Information
Quantum Computing
June 1, 2026 – Present
Generative AI and AI Agents with Amazon Bedrock
AWS
June 1, 2026 – Present
Introduction to OpenClaw
Other Advanced AI
June 1, 2026 – Present
Quickstart: LangSmith Essentials
Other Advanced AI
June 1, 2026 – Present
Data Science
IBM
June 1, 2026 – Present
Intro to Agent Observability
Other Advanced AI
June 1, 2026 – Present
OAO: A Deterministic Execution Runtime for Governed Multi-Agent LLM Systems
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's portfolio showcases a strong alignment with the target role of Generative AI Engineer, with projects heavily focused on multi-agent systems, RAG, and LLM orchestration. The diversity of projects (judicial, admission, data science, gaming) indicates adaptability and a broad interest in applying AI across various domains. However, the candidate's experience level is still early career, which might require mentorship and integration into a senior team's workflow.
Soft Skills & Operational Fit
The candidate demonstrates strong initiative and problem-solving skills through their diverse personal projects addressing real-world challenges (e.g., judicial backlog, admission automation). Their focus on observability, guardrails, and scalable orchestration indicates an operational mindset crucial for deploying robust AI systems. The open-source contribution highlights a collaborative and community-oriented approach.