---
title: "Parth Kulshreshtha - Associate AI Engineer | AI Research in Chennai | Tal"
description: "Meet Parth Kulshreshtha, Associate AI Engineer | LLM Evaluation & Agentic AI Systems | AI Research Team @ Centific based in Chennai. AI stack includes claude code, claude, and codex. Explore public work links including github."
image: "https://tal.club/meet/parth-kulshrestha/share-image"
---

# Parth Kulshreshtha on Tal

## Headline

Associate AI Engineer \| LLM Evaluation & Agentic AI Systems \| AI Research Team @ Centific

## About

I engineer and evaluate applied AI systems built around LLMs, multimodal models, and agentic workflows, with a focus on reliability and measurable performance\. As an Associate AI Engineer at Centific, my work has included LLM and RAG evaluation, multimodal quality assurance, model fine\-tuning, an environment for reinforcement learning with verifiable rewards, and AI microservices deployed on Azure\. Across these areas, I enjoy turning ambiguous problems into systems and workflows that can be tested, measured, and improved against real\-world data, failure cases, and changing requirements\. I’m interested in connecting with people building reliable LLM applications, agentic systems, and applied AI products\.

## Location

Chennai

## AI stack

claude code

claude

codex

hugging face

langgraph

mcp

## Work experience

Associate AI Engineer \| AI Research at Centific, Aug 2025 \- Present · 1 yr 1 mo, • Built LLM evaluation infrastructure: an LLM\-as\-judge framework for model\-written code, dimensional rubrics for judging AI agents on finance work, batch model serving on vLLM, and public benchmark runs through Inspect Evals\. • Built the screening stage of an agentic video\-annotation quality system: two\-pass VLM frame analysis, an async orchestrator that fans specialist agents across annotations, and tooling that scores agent findings against human\-reviewer actions\. • First\-authored a paper at ACM AI\-SQE 2026 \(co\-located with ICSE 2026\) on enterprise code evaluation, and co\-authored an ICML 2026 position paper on quality assurance in annotation pipelines\.

Associate Application Engineer \- Intern at Centific, Oct 2024 \- Jul 2025 · 10 mos, • Developed and optimized backend APIs using Python, Flask, and PostgreSQL, ensuring seamless data integration with frontend systems and improving system reliability\. • Designed and implemented scalable backend systems leveraging distributed task queues \(Celery, Redis\) to enable concurrent executions and improve overall system performance\. • Deployed AI services on Azure Kubernetes Service \(AKS\), containerizing models and integrating them into production pipelines with strong emphasis on CI/CD and testing\.

AI/ML Intern at LLMate, May 2023 \- Jul 2023 · 3 mos, Bengaluru, Karnataka, India, • Gained valuable experience as an AI/ML Intern for 2 months in a hybrid environment, successfully integrating AI into web and mobile applications across two projects\. • Developed a web app, AI Tutor, which functioned as a chatbot to answer student queries based on NCERT science books, aiding CBSE board exam preparation; additionally built a WhatsApp bot, Google Calendar Scheduler, which streamlined event scheduling by directly syncing meetings to Google Calendar, reducing user clicks\. • Enhanced teamwork skills, embraced new concepts, and witnessed significant personal growth\.

## Education

Bachelor of Technology \- BTech, Computer Science and Engineering, BML Munjal University

## Public links

- github: https://github\.com/that\-rookie\-parth

[View the original profile](https://tal.club/meet/parth-kulshrestha)

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