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 < 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