---
title: "Ayush Pratap Singh - SDE-Sytem Engineer in Pune City | Tal"
description: "Meet Ayush Pratap Singh, AI Systems Engineer @ TRDDC | Knight-Leetcode(2070) | DSA | Gen AI | Agentic AI | Enterprise Digital Twins based in Pune City."
image: "https://tal.club/meet/ayush-pratap-1/share-image"
---

# Ayush Pratap Singh on Tal

## Headline

AI Systems Engineer @ TRDDC \| Knight\-Leetcode\(2070\) \| DSA \| Gen AI \| Agentic AI \| Enterprise Digital Twins

## About

I build production\-grade AI systems that solve real enterprise problems — not demos, but deployable systems with measurable impact\. At TRDDC \(Tata's R&D division\), I work at the intersection of LLMs, retrieval systems, and agentic workflows: → Built a multimodal RAG pipeline \(text, audio, video\) that processes enterprise data at scale, cutting query latency by 40% → Designed an LLM routing system across GPT\-4, Llama\-3, and open\-source models — reducing inference costs by 35% without quality loss → Led agentic AI workflows for healthcare using AutoGen and CrewAI, accelerating prototype delivery → As an intern, shipped a full\-stack RAG document QA system processing 3,000\+ pages/day with 92% top\-3 retrieval accuracy I care about making AI systems efficient, cost\-aware, and actually useful in production — not just technically impressive\. Outside of work, I'm a competitive programmer \(LeetCode Knight, Top 5% globally, 800\+ problems solved\) and a deep believer that strong fundamentals make better AI engineers\. 📍 Pune \| Open to: AI Engineering, LLM Systems, AI Developer, Python Developer roles\.

## Location

Pune City

## Work experience

SDE\-Sytem Engineer at Tata Research Development and Design Centre \(TRDDC\), Aug 2024 \- Present · 2 yrs 1 mo, Pune District, Maharashtra, India, \- Led end\-to\-end development of a multimodal RAG system supporting audio, video, and text — enabling voice and text\-based Q&A over unstructured enterprise data\. \- Optimized vector retrieval using FAISS and ChromaDB, reducing query latency by 40% and improving response relevance at scale\. \- Designed an intelligent LLM routing system across GPT\-4, Llama\-3, and open\-source models — cutting inference costs by 35% while maintaining response quality\. \(Awarded: Special Initiative Award\) \- Led agentic AI workflows for healthcare use cases using AutoGen and CrewAI, accelerating prototype delivery timelines\. \- Mentored 2 interns, conducting code reviews and guiding system design decisions\. Tech Stack: Python · FastAPI · FAISS · ChromaDB · LangChain · LangGraph · AutoGen · CrewAI · OpenAI · Groq · HuggingFace

Research Intern at Tata Research Development and Design Centre \(TRDDC\), Jun 2023 \- Nov 2023 · 6 mos, Pune District, Maharashtra, India, \- Built and deployed a full\-stack RAG\-based document QA system processing 3,000\+ pages/day for enterprise use cases\. \- Benchmarked Llama\-2, GPT\-3\.5, and custom embeddings — achieving 92% top\-3 retrieval accuracy in internal evaluations\. \- Developed a React \+ Flask application enabling scalable document ingestion and querying workflows used by internal teams\. \- Presented system architecture and findings to stakeholders and clients; authored end\-to\-end technical documentation\. Tech Stack: Python · Flask · React\.js · LangChain · HuggingFace · Vector Databases

## Education

Bachelor of Technology \- BTech, Computer Science Engineering, Indian institute of information technology Nagpur

[View the original profile](https://tal.club/meet/ayush-pratap-1)

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