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Avinash Lodhi

@avinashlodhi

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AI/ML Engineer building production LLM, RAG, and agentic AI systems that ship reliable end-to-end products.

India

Message

What I'm looking for

I want to build production-grade LLM, RAG, and agentic AI systems—designing reliable pipelines and shipping REST APIs and deployments that are fast, scalable, and high-availability, with room to grow my impact end-to-end.

I’m an AI/ML Engineer with 1+ year of experience building and shipping production-grade LLM, RAG, and agentic AI systems for real-world applications. I specialize in turning complex AI ideas into fast, reliable products end-to-end.

At Hestabit Technology, I design and deploy production-grade LLM applications using LangChain and LangGraph, leveraging multi-step reasoning, tool use, memory, and state management. I build end-to-end RAG pipelines—from document ingestion and chunking strategies to embedding generation and FAISS indexing for semantic search and context-aware responses.

I also expose AI capabilities via RESTful APIs with FastAPI and deploy scalable LLM pipelines using Docker across cloud environments (including Vercel). I orchestrate multi-step AI workflows with N8N and Make.com, and I’m known for delivering end-to-end solutions that are high availability and performance-focused.

Experience

Work history, roles, and key accomplishments

Current

AI/ML Engineer

Current

Hestabit Technology

Dec 2025 - Present (8 months)

Designs and deploys production-grade LLM and agentic AI systems using LangChain and LangGraph, including multi-step reasoning and tool use. Builds RAG pipelines and exposes LLM capabilities via FastAPI REST APIs, deploying with Docker and Vercel and orchestrating workflows with N8N and Make.com.

AI/ML Intern

Hestabit Technology

Aug 2025 - Dec 2025 (4 months)

Developed RAG-based document Q&A systems and prompt engineering pipelines for NLP tasks such as summarization, classification, and structured data extraction using Pydantic output schemas. Assisted in integrating LLM capabilities into web applications and contributed to modular, scalable Python codebases within Agile/Scrum workflows.

RAG Prompt Engineering NLP Summarization Classification Data Extraction Pydantic Python Agile Scrum

Education

Degrees, certifications, and relevant coursework

ABES Engineering College

Bachelor of Technology, Computer Science Engineering

2022 - 2026

Grade: 8.1 / 10.0 (CGPA)

Pursuing a B.Tech in Computer Science Engineering with a CGPA of 8.1/10.0, covering Data Structures & Algorithms, Natural Language Processing, Machine Learning, DBMS, Computer Networks, System Design, and OOP.