---
title: "Garmit Pant - Software Development Engineer I in Bengaluru | Tal"
description: "Meet Garmit Pant, SDE-1 at Amazon | Ex-MathWorks | IIIT Delhi based in Bengaluru. AI stack includes claude code, claude, and kiro."
image: "https://tal.club/meet/garmit-pant/share-image"
---

# Garmit Pant on Tal

## Headline

SDE\-1 at Amazon \| Ex\-MathWorks \| IIIT Delhi

## About

Software engineer at Amazon building agentic AI systems that run in production at scale — currently on Alexa for Shopping, Amazon's AI assistant serving 129M\+ monthly users\. My work sits where LLM systems meet distributed backend engineering: multi\-agent orchestration, intent and tool routing, evaluation harnesses that keep agent quality honest, and the services underneath handling hundreds of millions of requests a month\. Before Amazon I worked in computer vision at MathWorks — semantic segmentation, object detection and tracking with vision foundation models — which is where I learned what it takes to move a model from a paper to something that holds up on real data\. I'm highly inquisitive and do my best work when exploration runs straight into hands\-on implementation\. Always happy to talk about agents, evals, or anything at the boundary of AI and systems\.

## Location

Bengaluru

## AI stack

claude code

claude

kiro

langchain

mcp

OpenRouter

## Work experience

Software Development Engineer I at Amazon, May 2025 \- Present · 1 yr 5 mos, Bengaluru, • Architected and delivered end\-to\-end agentic subscription management for Alexa for Shopping, Amazon's AI assistant \(129M\+ MAU\), replacing static help flows with live subscription data across 8\.5M\+ annual queries and 25\+ digital businesses\. • Designed and shipped MCP tools integrated with Amazon's centralized multi\-tenant subscription platform, federating 30\+ backend services to surface real\-time billing, renewal, and plan data conversationally\. • Built layered intent disambiguation for agentic tool routing, resolving cross\-domain conflicts to hold resolution to under 2 tool invocations per query and contain per\-query latency and inference cost\. • Drove end\-to\-end productionization of 20\+ agentic user actions from POC through phased rollout, and built an LLM\-as\-judge evaluation harness with configurable judge prompts to surface agent quality regressions before launch\. • Owned and led migration of the Prime Video subscription channel data service \(487M monthly requests, 1\.6B at peak\) off a legacy dependency, building an asynchronous validation framework that verified response parity at zero customer latency impact\. • Drove an overhaul of the unit\-testing framework across the entire hydrator test suite, refactoring dummy stubs into mock clients of downstream services so tests exercised real call paths rather than placeholder responses\. • Executed load testing across 6 peak\-simulation GameDays \(NA/EU/FE\) and drove capacity\-scaling analysis behind zero\-outage Prime Day 2025 traffic \(11\.2M customer visits\), including scaling a distributed ElasticSearch cluster from 4 to 20 data nodes\. • Architected the orchestration engine and agent scaffold for an internal multi\-agent AI platform \(now 22 agents and 29 skills across 2 teams\) that automates availability root\-cause analysis and weekly on\-call reporting, saving roughly 740 engineer\-hours per year\.

Software Engineer at MathWorks, Jul 2023 \- Aug 2024 · 1 yr 2 mos, Hyderabad, • Developed and validated an end\-to\-end object detection and tracking pipeline for video built on vision foundation models \(Grounding\-DINO, SAM, DeAOT\), with significant Python development — improving tracking accuracy by 8% and reducing user touchpoints by 50%\. • Improved semantic segmentation accuracy on hyperspectral imagery from 74% to 96% using U\-Net, through extensive data pre\-processing and post\-processing, augmentation, and hyperparameter optimization across MATLAB and Python\. • Built a parallelized multiprocessing data pipeline in Python that accelerated Radiative Transfer Modelling\-based atmospheric correction of \~650GB of satellite imagery by 4x — designing the workflow end to end, and driving significant C\+\+ code review and debugging\. • Engineered an internal operations dashboard \(React, Node\.js, Express, MongoDB\) with RESTful APIs and role\-based data models, reducing onboarding time by 30% for 500\+ employees\. • Contributed to the MATLAB community by solving 100\+ queries on the MATLAB Answers forum\.

EDG Intern at MathWorks, May 2022 \- Jul 2022 · 3 mos, Hyderabad, Telangana, India

Research Intern at MIDAS: Multimodal Digital Media Analysis Lab, Jan 2021 \- Oct 2021 · 10 mos

## Education

Bachelor of Technology \- BTech, Computer Science and Applied Mathematics, Indraprastha Institute of Information Technology, Delhi

High School Diploma, Science \(Non\-medical\), Delhi Public School Rohini

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

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