---
title: "Aayush Rai - Senior Software Engineer in Bengaluru | Tal"
description: "Meet Aayush Rai, Technical Lead based in Bengaluru. AI stack includes anthropic apis, claude code, and claude. Explore public work links including github and leetcode."
image: "https://tal.club/meet/aayush-rai/share-image"
---

# Aayush Rai on Tal

## Headline

Technical Lead

## About

Karbon Business relies on contributions to AI\-driven systems, microservices, and event\-driven architectures\. Delivered a high\-performing Master Data Service with 100\+ user\-facing APIs and AI\-powered extraction services, achieving over 90% accuracy through dynamic routing and OpenAI integration\. Enabled seamless inter\-service communication with AWS EventBridge and SQS while maintaining modularity and reliability with 90%\+ test coverage\. With a Computer Science degree from Medi Caps Institute of Technology and Management, expertise spans Python, Django, and cloud\-based architectures\. Dedicated to creating scalable, innovative solutions that align technology with organizational goals\. Passionate about leveraging AI and systems design to drive operational excellence\.

## Location

Bengaluru

## AI stack

anthropic apis

claude code

claude

codex

cursor

langchain

## Work experience

Senior Software Engineer at Give, Nov 2025 \- Present · 9 mo, Bengaluru, Karnataka, India

Senior Software Engineer at Karbon Business, Jan 2024 \- Nov 2025 · 1 yr 11 mos

Software Engineer at Karbon Business, Aug 2022 \- Dec 2023 · 1 yr 5 mos, \- Last 6 months: scaled MVP into a full accounting automation product; onboarded 250\+ beta customers and added two\-way sync with Zoho Books & Tally Prime\. \- Built backend on Django, exposing 200\+ user\-facing APIs \(DRF\) for bills, transactions, invoices, company profiles, reporting, and automation workflows\. \- Engineered AI\-powered document & transaction extraction/enrichment using OpenAI, Anthropic, and FinBox, delivering 90%\+ accuracy on bank, card, e\-commerce statements and bills\. \- Built a test bench for AI Agents/AI Models to evaluate approaches, improving accuracy tracking and enabling 3× faster deployments of better version\. \- Implemented event\-driven pipelines with AWS EventBridge \+ SQS to drive reliable bi\-directional sync with external accounting tools\. \- Containerized and shipped with Docker; set up Bitbucket CI/CD \(linting, tests, security scans\) and Terraform\-managed AWS \(ECS, RDS, S3, ECR, ElastiCache, CloudWatch, Secrets Manager\) → 2× faster releases & 90% fewer failures\. \- Maintained 90%\+ automated test coverage across 50K\+ LOC; upheld reliability with MTTR <12h \(P1\) and <2 days \(P2\)\. \- Built React UIs for the credit engine and prepaid card onboarding to streamline analyst and customer flows\. \- Shipped a RAG chatbot \(OpenAI \+ Pinecone\) answering 200\+ FAQs, reducing support effort\. \- Created a QA Chrome extension and an AI model test bench, enabling 3× faster evaluation and rollout of improved models\. \- Automated reporting, database maintenance, and sync tasks with Celery\.

Solution engineer at GAMMASTACK, Jun 2021 \- Aug 2022 · 1 yr 3 mos, Indore, Madhya Pradesh, India, • Design and Implemented one\-to\-one live chat for chat support\. • Implemented feature to calculate tax on order according to state and product category using Taxjar\. • Implemented product subscription feature which helps the user in recurring orders and payments\. • Implemented feature to onboard the seller\. • Automated seller biweekly payout using Cron Job and stripe\. • Implemented feature to show user payment methods, add a new payment method, or remove an existing payment method\. • Implemented UI designs in React for multiple websites\.

Software developer intern at ResoluteAI\.in, Dec 2020 \- Jun 2021 · 7 mos, Indore, Madhya Pradesh, India, • Migrated attendance management system\(based on face recognition\) from a monolithic architecture to microservice architecture\. • Implemented feature to synchronize local database with firebase real\-time database using GCP cloud function\. • Improved communication speed between microservice by 60% using Socket over HTTP\.

Computer Vision Intern at TDB\.ai, May 2020 \- Sep 2020 · 5 mos, Madhya Pradesh, India, • Improved total response time of multiple deep learning models by introducing threading\. • Implemented features like fall detection, intruder detection, fire detection, and alert\. • Trained and tested different deep learning models\. • Integrated the Deep Learning models with Django\. • Built the logic for a face recognition\-based attendance system\.

## Education

Bachelor of Technology \- BTech, Computer Science, Medi Caps Institute of Technology and Management \(Management\), A\.B\. Road, Pigdamber, Indore 453331

## Public links

- github: https://github\.com/aayushrai
- leetcode: https://leetcode\.com/Aayush\_rai

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

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