LangChain support agent across 3 business verticals.
Applied AI Engineer
Abhishek Bote
RAG, agents, and multimodal systems built for production workflows.
Research Study
RAG Hallucination Experiment
Study
300 stratified QA items
The paper tests whether retrieval quality changes hallucination, accuracy, citation correctness, and latency.
Open Research PaperSpeech, OCR, vision, and text in one assistant.
ML skill matching for a 50+ person workforce.
AI career platform on Vercel and Supabase.
Profile
AI systems that are measured, grounded, and shipped.
Ground
RAG pipelines, retrieval quality, hallucination-aware evaluation.
Automate
Agent routing, workflow automation, structured intent extraction.
Ship
FastAPI, AWS Lambda, GCP, Supabase, CI/CD, production monitoring.
Experience
Execution record
AI Engineer Intern
Production support agent100K+
requests processed
300+
daily active users
-40%
infrastructure cost
LangChain, Perplexity API, AWS Lambda, S3, Amplify
AI Software Engineer
Multimodal AI and MLOps5K+
daily sessions
3
AI products shipped
20m
deployment cycle
FastAPI, GCP, TensorFlow, OpenCV, GitHub Actions
Junior Software Engineer
Analytics automation23%
backlog reduction
20h
saved monthly
ETL
risk field checks
Python, SQL, Power BI, SharePoint, Excel
01
Mitigating LLM Hallucinations with RAG
Pre-registered experiment testing how retrieval quality changes factual accuracy, hallucination, citations, and latency.
300 QA items
C1/C2/C3 comparison
validated rubric
Read paper
02
PolyLingua LoRA Translation
English-to-Indic LLM translation pipeline built with a 1.5M sentence corpus and PEFT/LoRA fine-tuning.
Gemma + LLaMA
20% lift
GitHub
03
AI Debugger
TypeScript debugging workspace for AI-assisted issue triage, code context review, and faster developer feedback loops.
TypeScript
debug workflow
GitHub
04
Gemini Voice Assistant
Python voice agent connecting speech-to-text, Gemini, tool functions, structured logs, and text-to-speech.
STT -> LLM -> TTS
tool execution
GitHub
05
BLUD AI
AI career roadmap platform turning user goals into personalized plans through a multi-step Groq LLM pipeline.
35K+ queries
80+ roadmaps
99% uptime
LinkedIn project
Skills
Core stack
AI Systems
RAG, agents, LangChain, LangGraph, CrewAI, Hugging Face, OpenAI API, Gemini, Groq
Modeling
PyTorch, TensorFlow, Scikit-learn, OpenCV, LoRA/PEFT, XGBoost, RapidMiner
Backend
Python, FastAPI, Node.js, Next.js, TypeScript, SQL, REST APIs, microservices
Cloud and Data
AWS Lambda, S3, Amplify, GCP, Azure AI Foundry, Docker, GitHub Actions, Power BI, Supabase
Education
Academic foundation
Pace University
M.S. Information Systems | New York, NY | GPA 3.85/4.0 | 2024 - 2026
Savitribai Phule Pune University
M.Sc. Computer Science | Pune, India | GPA 9.15/10 | 2021 - 2023
Savitribai Phule Pune University
B.Sc. Computer Science | Pune, India | 2017 - 2021
Certifications
Validated training
Google Cloud
Advanced Generative AI Agents Developer
NVIDIA
Fundamentals of Deep Learning
HackerRank
Python Advanced and SQL Advanced
Leadership
Community and technical programs
Google Developers Group
Organizer and technical lead supporting 500+ attendees across workshops, speaker sessions, and live demos.
Perplexity Campus Partner
Selected from the top 5% of applicants; ran workshops reaching 300+ students.