Chetan Satkar

AI / ML Engineer • Generative AI Engineer • Agentic AI Engineer

Pune, IN.

About

Highly accomplished AI/ML Engineer with over 2 years of experience, specializing in designing and deploying production-grade Generative AI and Agentic AI systems. Proven expertise in developing multi-agent workflows and LLM pipelines using LangChain, LangGraph, and LlamaIndex, coupled with deep knowledge in RAG and fine-tuning techniques (LoRA/QLoRA/PEFT). Adept at leveraging state-of-the-art LLMs and MLOps practices (Docker, Kubernetes, AWS) to transform AI prototypes into scalable, impactful solutions that solve complex business problems.

Work

Hirehut

|

GenAI Engineer

Pune, Maharashtra, India

→

Summary

Leads the design and deployment of production-grade Generative AI and Agentic AI systems, optimizing multi-agent orchestration and LLM pipelines for automated candidate evaluation and complex problem-solving.

Highlights

Architected and deployed an Agentic AI Interviewer platform using LangGraph, orchestrating multi-agent workflows with adaptive difficulty logic and LLM-driven scoring to automate candidate evaluation.

Developed a JEE-level Math Monitor ChatBot with a Hybrid RAG pipeline, integrating dense semantic search and keyword-based retrieval using FAISS and HuggingFace embeddings for precise problem-solving.

Engineered LLM evaluation engines to generate structured JSON outputs, significantly reducing manual review effort for automated assessment and feedback.

Enhanced LLAMA model relevance and response quality by applying LoRA/QLORA/PEFT fine-tuning techniques for domain-specific hiring tasks.

Ensured reliable, production-grade performance of AI agent systems by containerizing and deploying them with Docker and Kubernetes.

Adify AI

|

AI/ML Engineer

Bangalore, Karnataka, India

→

Summary

Developed and deployed intelligent AI systems, including an Event Booking Agentic AI System and a Patient-Doctor Management System, leveraging AWS services and robust data models for scalable and secure operations.

Highlights

Architected and deployed an intelligent Event Booking Agentic AI System on LangChain, automating multi-step booking workflows via tool-calling agents and reasoning chains.

Developed a full-stack Patient-Doctor Management System using Django, ensuring secure medical record handling, user authentication, and scalable backend architecture.

Designed and implemented robust REST APIs with Flask and FastAPI, facilitating seamless integration of medical data services with frontend and third-party platforms.

Engineered production-ready data models and applied strong software engineering practices for secure management of sensitive patient and doctor records.

Optimized system scalability and cost-efficiency by integrating AWS services (Lambda, S3) for serverless workflows and reliable storage.

Contributed to AI-driven healthcare features by collaborating on model evaluation and data preprocessing pipelines using Python (Pandas, NumPy, Scikit-learn).

Adify AI

|

AI/ML Intern

Bangalore, Karnataka, India

→

Summary

Analyzed hospital ER datasets and developed machine learning models on real-world medical data, providing actionable insights and improving model performance.

Highlights

Conducted in-depth data analysis on Hospital ER datasets using Python (Pandas, NumPy) and SQL, generating actionable insights for strategic healthcare decision-making.

Developed and rigorously evaluated machine learning models on real-world medical data, enhancing model performance through advanced preprocessing, feature engineering, and Scikit-learn.

Education

Savitribai Phule Pune University

Pune, Maharashtra, India
→
Bachelor of Engineering (B.E.) Engineering

Languages

English

Certificates

Introduction to Generative AI

Google Cloud

Data Analytics Internship Certificate

Intern Meets Edu Tech Pvt. Ltd.

Skills

Programming Languages & Tools

Python, NumPy, Pandas, SQL, SQL Server, CTEs, Window Functions, Stored Procedures, Indexing.

Core AI/ML

Machine Learning, Deep Learning, Natural Language Processing (NLP), Computer Vision, Regression, Classification, Clustering.

Generative AI & Agentic AI

Large Language Models (LLMs), LangChain, LangGraph, LlamaIndex, Retrieval-Augmented Generation (RAG), Vectorless RAG System, Multi-Agentic AI Workflow, AI Agents, Model Context Protocol (MCP), Prompt Engineering, Fine-tuning (LoRA), QLORA, PEFT.

AI Models & Frameworks

GPT-4, LLaMA, Gemini, Hugging Face Transformers, TensorFlow, PyTorch, Scikit-learn, OpenCV.

Vector Databases & Embeddings

FAISS, Pinecone, ChromaDB, Vector Databases, Embeddings, Tokenization.

MLOps & Cloud Technologies

Docker, Kubernetes, AWS Lambda, AWS S3, AWS SageMaker, MLflow, CI/CD, Serverless, Git.

Backend Development & APIs

FastAPI, Flask, Django, SQL, Distributed Computing.

Agentic IDEs & Tools

Cursor, Antigravity, Claude Code, Codex, AI-Native Development.

Frontend Development

HTML, CSS, Bootstrap.

Projects

AI Interviewer for HireHut – Agentic AI System

→

Summary

Built a scalable multi-agent AI interview platform using LangGraph with adaptive difficulty logic, LLM-driven answer scoring, and structured JSON feedback for automated candidate assessment.

Math Monitor ChatBot - JEE Level Problem Solver

→

Summary

Built an intelligent JEE-level math problem solver using a Hybrid RAG approach, combining dense semantic search with keyword-based retrieval to deliver accurate, context-aware solutions for complex mathematical problems.

Event Booking Agentic AI System – LangChain

→

Summary

Built an autonomous agent-based event booking system on LangChain, using tool-calling agents and reasoning chains to automate multi-step workflows (search, availability, reservation, confirmation), exposed via a Flask REST API with production-grade deployment.

Patient-Doctor Management System

→

Summary

Developed a full-stack Django web application for managing patient-doctor records with secure data handling and a scalable backend architecture.

Hospital ER Data Set Analysis

→

Summary

Analyzed large hospital ER datasets using Python (Pandas, NumPy) and SQL; built Power BI dashboards to deliver actionable insights for healthcare data-driven decision-making.

Predictive Maintenance using ML & Flask API

→

Summary

Developed an ML model to predict equipment failures using operational data, reducing downtime; deployed a Flask REST API with real-time prediction endpoints and JSON-based integration.