---
title: "Divyansh Jain - Senior Software Engineer (AI) | AI Agents, GenAI, LLMs, RAG, MCP, Python, GCP in Bengaluru | Tal"
description: "Meet Divyansh Jain, Senior AI Engineer | Building AI Agents that manage money @ Zeni | GenAI, LLMs, RAG, MCP | Python, GCP | ex-Tech Lead (13 members) | 3× 0→1 based in Bengaluru. AI stack includes claude code, claude, and cursor. Explore public work links including github and leetcode."
image: "https://tal.club/meet/divyansh-jain-1/share-image"
---

# Divyansh Jain on Tal

## Headline

Senior AI Engineer \| Building AI Agents that manage money @ Zeni \| GenAI, LLMs, RAG, MCP \| Python, GCP \| ex\-Tech Lead \(13 members\) \| 3× 0→1

## About

I build production AI agents — the kind that ship, run reliably, and replace real human workflows\. Senior SWE \(AI\) at Zeni, the AI bookkeeping platform for startups\. What I shipped recently: → Credit Assessment Agent \(Vertex AI Agent Builder\): scores tenants from cash flow, P&L and balance sheet before card approval\. Unlocked 6\.7× scale for Zeni's card program \(\~$80M projected volume, \~$2\.4M gross interchange\) and automated \~2,000 hrs/yr of underwriting\. → Internal MCP server \(Google ADK\): exposes Zeni's financial data as agent tools — LRU\-cached, feature\-gated by tenant\. Agentic RAG in production: the agent decides what context it needs and retrieves it on demand\. → Zeni Cards, 0→1: issuance, ledger, interchange \+ cashback engine\. $12M volume year one, 99\.9999% uptime, p95 < 200ms\. Before Zeni: Tech Lead at LimeChat — built the WhatsApp Flow Builder 0→GA in 3 months, onboarded 30\+ D2C brands in 6, scaled to 100M events/day at 99\.97% uptime, led 13 engineers across 2 pods, cut AWS spend 40%\. 7 years across fintech, D2C and telecom\. Three 0→1 launches\. Stack: Python · GCP · Google ADK · Vertex AI Agent Builder · MCP · LangChain · LLMs · GenAI · Agentic RAG · Sentence Transformers · embedding quantization · prompt engineering · event\-driven, multi\-tenant backends \(Factory/Strategy/Adapter\) · Kubernetes · AWS · Django · FastAPI · Elasticsearch · Postgres Open to Staff / Principal AI Engineer and Tech Lead \(AI\) roles where agents do real work, not demos\. 📩 divyansh\.jain\.2015@gmail\.com

## Location

Bengaluru

## AI stack

claude code

claude

cursor

notebooklm

openai

claudecode

## Work experience

Senior Software Engineer \(AI\) \| AI Agents, GenAI, LLMs, RAG, MCP, Python, GCP at Zeni, May 2024 \- Present · 2 yrs 4 mos, Pune, Maharashtra, India, Building AI agents and the backend systems that power them at Zeni, the AI bookkeeping platform for startups\. CREDIT ASSESSMENT AGENT — Vertex AI Agent Builder \- Scores every tenant from cash flow, P&L, balance sheet before card approval \- Unlocked 6\.7× customer scale \(75 → 500\+ tenants\); \~$80M projected volume, \~$2\.4M gross interchange \- Automated \~2,000 hrs/yr of underwriting \- Internal MCP server on Google ADK exposes financial data as agent tools — LRU\-cached, feature\-gated by tenant; agentic RAG in production ZENI CARDS — 0→1, Debit & Credit \- First issued cards: issuance, ledger, interchange \+ cashback engine, spend analytics \- \~$12M annual volume; monthly volume \+36% in Q1; 99\.9999% uptime, p95 < 200ms \- One card engine across debit and credit \(Strategy pattern\); webhook processor factory for 6\+ Unit \(BaaS\) event types; multi\-tenant namespace isolation MARK BILL AS PAID — Spend Management \- Saved \~$180K/yr; cut reconciliation 5 hrs/month across 150\+ controllers; QBO sync Tech: Python · GCP · Google ADK · Vertex AI Agent Builder · MCP · LangChain · Unit\.co · QuickBooks Online

Senior Software Engineer at Google, Apr 2024 \- May 2024 · 2 mos, Bengaluru

SDE3 \| Python, LangChain, Sentence Transformers, ML Retrieval, MongoDB at goGLOCAL, Oct 2023 \- Apr 2024 · 7 mos, Mumbai, Maharashtra, India, Led the GES \(Global Expansion Strategy\) and PLS \(Product Level Strategy\) initiatives — GTM tooling for Indian brands entering international markets\. Managed 3 FTEs\. \- Built semantic retrieval \(Sentence Transformers \+ embedding quantization\) matching products to international market categories — foundation of the recommendation pipeline \- Consolidated 8 microservices into one workflow: 10× faster, report creation 12 hrs → 1 hr \- Cut cloud costs 70% \(bare\-metal migration\) \- Multi\-modal listing pipeline: LangChain \+ OpenAI orchestration, Detectron2/YOLO image classification

Technical Lead \| Python, Django, AWS, Conversational AI, RASA, Observability at LimeChat, Jan 2022 \- May 2023 · 1 yr 5 mos, Led 13 engineers across 2 pods\. Shipped WhatsApp Flow Builder 0→GA in 3 months; 30\+ D2C brands in 6; 100M events/day at 99\.97% uptime; AWS cost −40%\. OUTBOUND TEAM \- Flow Builder \+ Conversational AI \- Shipped 2\-way conversational AI bots on the RASA framework \(Deep Learning \+ NLU\) — a first in the chatbot industry at the time\. Automated 90%\+ of inbound chat traffic; campaigns ran some of the highest conversion rates in D2C \- Built Flow Builder 0→GA in 3 months — brands create custom interactive flows on WhatsApp and Instagram; lifted customer satisfaction and retention by up to 10% \- Designed LLD / HLD to handle 100M\+ events/day \- Event\-driven architecture with Factory and Adapter design patterns for maintainability \- Onboarded 30\+ D2C brands within 6 months of launch SERVICES TEAM \- Platform Stability, Cost, Observability \- Cut AWS cost by 40% via Kubernetes capacity planning and RDS Aurora IO optimization \- 99\.97% uptime across all apps \- Centralized logging on the EFK stack — 10\+ applications, designed for 1TB/day ingestion \- ALBs with WAF \- secured systems against DDoS and brute\-force attacks \- Cut bug resolution time by 70% with Prometheus \+ Grafana \+ New Relic monitoring and Slack alerts \- Optimized analytics SQL queries by 50× using query plans, partitioning, and indexes Team & Process \- Managed two teams via ClickUp; tracked sprint velocity and burndown \- Code quality gates with Pylint \+ SonarQube \+ Jenkins \(>80% coverage\) \- DSMs, weekly planning, retros, monthly 1\-1s

Data Analytics Engineer \| Python, Django, Kubernetes, PostgreSQL at LimeChat, Jun 2021 \- Dec 2021 · 7 mos, Led LimeKit team of 5 people to implement analytics and background jobs ● Designed analytics architecture from scratch, enabling loading rapid insights into all the products ● Introduced RBMQ with Celery for asynchronous processing of weekly analytics ● Worked on MVP of Flow Builder ● Designed a Load testing framework ● Mentored 5 interns

Software Engineer \| Java, Spring, Kubernetes, Elasticsearch at Thales, Apr 2021 \- Jun 2021 · 3 mos, Member of the ACS \(Apps Common Services\) team, building common features for all the applications IAM ● Automated keycloak using Ansibles and Helm, enabling the deployment of this service over distributed systems with a single command ● Secured Tableau using SAML, centralising security layer over distributed systems ● Implement WDC for Tableau to secure pushing data CONFIG SERVER ● Implemented end to end a spring app to save and centralise configurations of distributed systems\. Enabled the user to just update config at one place and broadcast over all the systems

Associate Software Engineer \| Java, Elasticsearch, Hadoop, Python, Big Data at Thales, Jul 2019 \- Apr 2021 · 1 yr 10 mos, Member of the RAF\(Reflex Analytics Fabric\) team, working on building a No code platform for Big Data CDAP ● Worked on ingestion plugins for Elasticsearch, enabling pushing into indexes, automating index creation over multiple versions of Elasticsearch ● Created a marketplace of all plugins using Python and Shell scripts, automated pushing the required plugins to each client RAF\-POV ● POV of the RAF product, showcasing the TTV of the product ● Created big data pipelines using Hive, Scala, Spark ● Worked with 1\.5 TB data per hour \(18B rows\) ● Designed and optimised Big Data pipelines to process whole Mumbai's network traffic in just an hour and provide detailed insights into it SECURITY ● Enhance security layer of Elasticsearch to provide RBAC over CRUD operations ● Directly contributed to OpenSource Opendistro framework ● Integrated with LDAP, Kerberos and Ranger ● Deployed it over distributed systems ● Created a detailed manual for clients over how to use the plugins

## Education

Bachelor of Engineering, Computer Engineering, Thapar Institute of Engineering & Technology

General Management Program, Business Administration and Management, General, Stoa

## Public links

- github: https://github\.com/divyanshh
- leetcode: https://leetcode\.com/divyanshh\_

[View the original profile](https://tal.club/meet/divyansh-jain-1)

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