---
title: "Aneesh Gupta - Software Engineer in Bengaluru | Tal"
description: "Meet Aneesh Gupta, Backend Engineer @ Equiti | Building infrastructure for AI agents | Java · Spring Boot · Python · Microservices · Distributed Systems · Agentic AI · LLMs/RAG | based in Bengaluru. AI stack includes claude code, cursor, and hermes agent. Explore public work links including github."
image: "https://tal.club/meet/aneesh-gupta/share-image"
---

# Aneesh Gupta on Tal

## Headline

Backend Engineer @ Equiti \| Building infrastructure for AI agents \| Java · Spring Boot · Python · Microservices · Distributed Systems · Agentic AI · LLMs/RAG \|

## About

I build infrastructure for AI agents — and I ship it in the open\. Agents are starting to act for us: spending money, calling APIs, holding credentials, browsing as us\. The systems that make that observable, affordable, and safe enough to deploy are what I build\. ▪ Chancery \(building now\) — an open\-source identity provider for AI agents: identity, sealed credentials, scoped delegation, and revocation, with every action attributed by construction\. Single Go binary, Apache\-2\.0, MCP\-first\. ▪ Conduit \(open source\) — an on\-prem LLM gateway: per\-engineer cost attribution, hard budgets, and egress governance, without ever storing prompts\. ▪ BugBountyAI — an autonomous multi\-agent security\-research platform: the LLM proposes, deterministic gates dispose\. Backend engineering — Java, Python, distributed systems — pointed at making agents trustworthy enough to actually ship\. Open to backend / applied\-AI roles, founding\-engineer opportunities, or building with anyone in the agent space\. → aneeshgupta709@gmail\.com Java · Spring Boot · Python · Go · Microservices · distributed systems · LLMs · RAG · multi\-agent systems · Postgres · Redis · Kafka · Kubernetes · AWS/OCI

## Location

Bengaluru

## AI stack

claude code

cursor

hermes agent

langchain

langgraph

ollama

## Work experience

Software Engineer at Equiti, Oct 2025 \- Present · 11 mos, Bengaluru, \- Architected a hybrid withdrawal risk assessment platform that combines ML\-based behavioral analytics with a rule\-engine framework to generate real\-time risk scores, enabling intelligent transaction evaluation and establishing a path toward replacing manually maintained static rules with adaptive, self\-learning models\. \- Architected and delivered a low\-latency payment processing framework for deposits and transfers, leveraging asynchronous workflow orchestration and CRM transaction optimization to reduce end\-to\-end latency from ∼20s to &lt; 3s while improving throughput and platform scalability\.

Member of Technical Staff at Oracle, Jun 2023 \- Sep 2025 · 2 yrs 4 mos, Bengaluru, Karnataka, India, USER MESSAGING SERVICE\(UMS\) \- Designing a self\-healing AI module for UMS engine using LLMs to monitor live logs and provide automated feedback and take corrective actions\. \- Optimized queueing using Transactional Event Queues \(TEQ\) and dynamic thread management, reducing cluster waits from 60 70% to under 10%\. \- Built a Google Cloud Messaging \(GCM\) simulator for high\-load testing and latency reduction

## Education

Bachelor of Technology, Computer Engineering, National Institute of Technology Rourkela

## Public links

- github: https://github\.com/anee769

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

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