---
title: "Dileep Varma - Senior Software Engineer in Bengaluru | Tal"
description: "Meet Dileep Varma, Software Development Engineer || Fullstack Developer || Agentic AI || {Java, javascript, Springboot, Python, React, sql, nosql, AWS and Software Design} || AI & Blockchain || Innovation || NITW ’21 based in Bengaluru. AI stack includes claude code, codex, and langgraph. Explore p..."
image: "https://tal.club/meet/dileep-varma/share-image"
---

# Dileep Varma on Tal

## Headline

Software Development Engineer \|\| Fullstack Developer \|\| Agentic AI \|\| \{Java, javascript, Springboot, Python, React, sql, nosql, AWS and Software Design\} \|\| AI & Blockchain \|\| Innovation \|\| NITW ’21

## About

I’m a Senior Software Engineer with 5\+ years of experience designing and scaling distributed systems and AI\-driven platforms powering millions of users globally\. I specialize in backend architecture, event\-driven systems, and cloud\-native infrastructure — building high\-performance, fault\-tolerant systems with measurable business impact\. Currently at Visa, I architect and own AI\-powered marketing and compliance platforms supporting global payment infrastructure\. My work includes: \- Built a PostgreSQL\-backed GCRA rate limiter for shared multi\-LLM infrastructure processing 100M\+ tokens daily \- Designing real\-time orchestration systems with worker pools, distributed queues, and retry/DLQ mechanisms \- Building SSE\-based streaming pipelines for low\-latency AI interactions \- Implementing RAG workflows using semantic search \(pgvector\) \- Delivering AI\-driven tear sheet generation 90% faster, with \~95% accuracy across 100\+ products and regions \- Driving $1\.5M\+ annual operational savings Previously at Publicis Sapient, I delivered enterprise\-scale systems for global clients including Marriott International, Circle K, and Albertsons\. Key contributions: \- Built fault\-tolerant distributed systems with 99\.99% uptime \- Optimized high\-QPS APIs and event\-driven microservices, reducing latency 40%\+ \- Accelerated bulk data pipelines by 45% and reduced cloud storage costs 18% \- Developed mobile/web features driving 30–40% engagement growth I also contributed to CoreAI, Publicis Groupe’s marketing intelligence platform, building cloud\-native AI services processing 650B\+ daily bid events to power audience targeting and campaign automation\. My engineering foundation began at National Institute of Technology, Warangal, where I led a computational fluid dynamics research project implementing the Lattice Boltzmann Method in Python to solve Navier–Stokes equations — shaping my systems\-thinking approach to scalability and performance\. Beyond engineering, I’m passionate about digital art, open source, Agentic systems, blockchain, and DeFi\. My artwork was featured at NFT\.NYC’s Times Square exhibition, and I actively contribute to tech inclusion initiatives and NGO\-led fundraising efforts\. I’m open to opportunities in backend engineering, distributed systems, and AI platform roles \(Senior SWE / SDE2 / L4–L5\)\. 📩 dileepvarmavirodhula@gmail\.com 💻 github\.com/Nero007x Tech: Java \| Spring Boot \| Kafka \| Distributed Systems \| Microservices \| AI & RAG \| SSE \| AWS \| Azure \| GCP \| PostgreSQL \| MongoDB \| Kubernetes \| React \| React Native \| Python \| System Design

## Location

Bengaluru

## AI stack

claude code

codex

langgraph

langsmith

mcp

huggingface

## Work experience

Senior Software Engineer at Visa, Aug 2025 \- Present · 1 yr 3 mos, Bengaluru, Karnataka, India, \- Distributed Orchestrator: Architected a fault\-tolerant Tear\-Sheet pipeline using ARQ worker pools, Redis\-based task queues and pub/sub messaging, and automated retry strategies with dead\-letter queues, achieving a 0\.0015% task failure rate\. \- Orchestrated asynchronous LLM, file ingestion, conversion services with SSE streaming, reducing generation time by 90% and delivering $1\.5M–$2M in annual operational savings for Visa Marketing Services\. \- Visa Configuration Manager: Designed and implemented automated BIN provisioning workflows across VisaNet’s CORE and CONFIG systems, automating 900\+ parameter configurations and reducing client onboarding at Visa by 80% for 100\+ Entities\. \- Express Licensing: Engineered an integration layer with asynchronous APIs, schedulers, and event\-driven sync to automate AML/OFAC compliance for Visa issuers, reducing licensing from 122 days to 10 days\. \- File Ingestion &Data Source: Led multi\-format file ingestion with S3\-based storage and SHA\-256 validation, with session\-isolated retrieval and data sources tracking for 100% auditability\. \- Cybersecurity Compliance: Directed SSDLC, PCI\-DSS, and OWASP compliance through penetration testing, security scans, and threat modeling, and reduced vulnerabilities by 40% for a VisaNet config platform, preventing 25\+ breaches\.

Software Development Engineer L2 \| Java EE, Springboot, Python, FastAPI, ReactJs, NextJs at Publicis Sapient, Oct 2021 \- Jun 2025 · 3 yrs 9 mos, Bangalore Urban, Karnataka, India, — Architected an AI\-driven validation system \(Bod\-hi AI Service\) automating asset metadata compliance checks for 5,000\+ assets monthly with 98% precision and eliminating 30\+ hours of weekly manual review\. — Built GCR Domain Service using Java, Springboot and PostgreSQL, managing CRUD operations across four micro\-modules; implemented B\-tree indexing and asynchronous batch handlers, boosting query performance by 35%\. — Refactored event routing logic \(Content Event Manager\) using Azure Event Hub for 15\+ event types, reducing delivery latency by 40% and increasing throughput by 25%\. — Overhauled metadata batch storage system using parallel write strategies and chunked data serialization, accelerating bulk write operations by 45% and reducing Azure Blob storage costs by 18%\. — Spearheaded the end\-to\-end development of an automated fuel rewards system \(INGO Free Liters\) for Denmark/Sweden, boosting customer acquisition by 15% and revenue by 20%\. — Integrated Lingo\-Hub with CI/CD pipelines for automatic translation updates and implemented i18n libraries \(react\-i18next\) across mobile applications, leading to a 30% growth in global user engagement\. — Designed and streamlined a robust microservices framework \(Partner Collaboration Hub\) using Java Spring Boot, achieving 99\.99% system reliability and improving analytics efficiency by 30% for 200\+ retail partners\. — Led development of a shared UI library of 200\+ components using Storybook and integrated into the design system, enabling cross\-team collaboration, and reducing design\-to\-development cycle time by 35%\. — Scaled deployment workflows using Helm charts and Kubernetes Operators for 20\+ microservices; achieved a 40–50% reduction in deployment time and improved system resilience via auto\-scaling/self\-healing configurations\.

Software Development Engineer L1 \| Java, RESTAPI, RDBMS, ReactJs Kafka at Publicis Sapient, Jun 2021 \- Oct 2021 · 5 mos, Bengaluru, Karnataka, India, — Revamped REST API endpoints by implementing server\-side pagination, efficient indexing, and query caching using Redis, resulting in a 30–50% improvement in data\-intensive operations\. — Pioneered higher\-order components and custom hooks in React architecture, enhancing reusability and reducing front\-end feature delivery time by 40%\. — Optimized Marriott web page performance using Blue Triangle analytics, reducing load times by 20%, increasing speed scores by 20\+ points, and lowering bounce rates by 10%\. — Accelerated data access velocity by 98% in an integration pipeline by reducing query execution time from 1 minute to 10 seconds through query optimization\. — Enhanced accessibility by implementing WCAG 2\.1 compliance \(text scaling, contrast optimization\), improving metrics by 30% and user engagement by 40%\.

Simulating Fluid Flow Around Obstacles using Lattice Boltzmann Method \(University Project\) \| Python at National Institute of Technology Warangal, Mar 2020 \- Apr 2021 · 1 yr 2 mos, Warangal, Telangana, India, \- Developed a Python\-based simulation tool implementing the Lattice Boltzmann Method \(LBM\) to model fluid flow around a cylindrical obstacle with over 95% alignment to theoretical predictions\. \- Numerically solved the Navier–Stokes equations, translating advanced fluid dynamics models into efficient Python algorithms\. \- Ran 50\+ simulations across a wide Reynolds number range to analyze laminar flow transition and vortex shedding behavior\. \- Optimized matrix operations with NumPy, reducing simulation runtime by 30% and enabling scalability to higher\-resolution domains\. \- Visualized fluid dynamics patterns using Matplotlib, achieving less than 5% deviation from benchmark results in laminar regimes\. \- Gained hands\-on expertise in scientific computing, computational physics, numerical methods, and algorithm optimization\.

## Education

Bachelor of Technology \- BTech, Mechanical Engineering, National Institute of Technology warangal

Higher Secondary Certificate, science, Jawahar Navodaya Vidyalaya \- JNV

## Public links

- github: https://github\.com/nero007x

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

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