---
title: "Aryan kumar - Forward Deployed Engineer in Bengaluru | Tal"
description: "Meet Aryan kumar, AI/ML | Python, SQL, Agentic AI, RAG, GNNs | Building Intelligent Systems with LLMs & Machine Learning | Open to Entry Level Roles based in Bengaluru. AI stack includes aistudio, claude code, and codex. Explore public work links including github."
image: "https://tal.club/meet/aryan-kumar-17/share-image"
---

# Aryan kumar on Tal

## Headline

AI/ML \| Python, SQL, Agentic AI, RAG, GNNs \| Building Intelligent Systems with LLMs &amp; Machine Learning \| Open to Entry Level Roles

## About

AI/ML Engineer specializing in Generative AI, Agentic AI, and Voice AI systems, with hands\-on experience building and deploying production\-grade AI solutions for real\-world clients\. Currently a Forward Deployed Engineer Intern at Agentic Universe, configuring voice AI agents for BFSI clients handling 25K–30K\+ outbound calls/day, working directly with clients to improve agent performance — contributing to a 50–60% lift in lead\-to\-conversion rates\. Previously built an Industrial AI QualityOps Copilot \(Detectron2, CAD\-based defect detection\) as an AIML Intern at Zero Zeta\. Project experience: RAG systems \(LlamaIndex, Qdrant\), multi\-agent workflows \(LangGraph\), and Graph Neural Networks for cybersecurity \(98% recall, 300K\+ records\)\. Skills: Python, PyTorch, LangGraph, LlamaIndex, RAG, Agentic AI, Voice AI \(TTS/STT\), Computer Vision, GNNs, Qdrant, Supabase, REST APIs\.

## Location

Bengaluru

## AI stack

aistudio

claude code

codex

cursor

mcp

openai

## Work experience

Forward Deployed Engineer at Agentic Universe, Sep 2026 \- Present · 1 mo, Bengaluru, • Configure and maintain production voice AI agents handling 25K\-30K\+ outbound calls per day per client for BFSI clients, owning agent setup, conversation flow design, and call\-handling parameters at scale • Act as the client\-facing technical contact across accounts, translating evolving client expectations into configuration and prompt updates that lifted lead\-to\-conversion rates by 50% • Developed an end\-to\-end understanding of the voice backend system, including how the STT, LLM, and TTS layers work together to deliver live calls • Monitor system\-level agent performance using AWS CloudWatch logs and metrics to catch anomalies before they affect calls • Diagnose live issues and perform root cause analysis \(RCA\) backed by CloudWatch log evidence, so clients get clear, proof\-based explanations of what went wrong and how it was fixed

AIML Intern at Zero Zeta, Jul 2026 \- Sep 2026 · 3 mos, Remote, • Developed an Industrial AI QualityOps Copilot that extracts dimensions/tolerances from DXF/DWG CAD files and uses Detectron2\(ResNet\-50 \+ Mask R\-CNN\) for component detection and contour\-based geometric measurement from camera images\. • Built an end\-to\-end CAD\-to\-image measurement and tolerance\-validation pipeline, using calibrated pixel\-to\-mm conversion and automated feature mapping to generate dimension\-level PASS/FAIL assessments, and deployed the solution as a production web application through direct client collaboration

## Education

Bachelor of Engineering \- BE, Artificial intelligence and machine learning, nitte meenakshi institute of technology

12, science, kendriya vidyalaya

## Public links

- github: https://github\.com/AryanPandey72

[View the original profile](https://tal.club/meet/aryan-kumar-17)

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