---
title: "Shubham Gupta - SDE 2 in Bengaluru | Tal"
description: "Meet Shubham Gupta, Backend Engineer · ~4 YOE | Java · Go · Kafka · Spring Boot | Distributed Systems & LLM Platform Infra based in Bengaluru. AI stack includes claude code, claude, and cursor. Explore public work links including github, leetcode, and codeforces."
image: "https://tal.club/meet/shubham-gupta-16/share-image"
---

# Shubham Gupta on Tal

## Headline

Backend Engineer · \~4 YOE \| Java · Go · Kafka · Spring Boot \| Distributed Systems & LLM Platform Infra

## About

I design and scale distributed backend systems — event\-driven pipelines, multi\-tenant platform services, and ML/LLM infrastructure\. Currently at Locus as SDE 2, previously built ML platform infra at Tekion Corp and owned the Ferry Booking vertical at Tiket\.com \(serving millions of users\)\. Core strengths: high\-throughput systems, observability, async architectures, and end\-to\-end ownership from design to production\. LeetCode Top 2% globally \(rating 2152\) \| Open to backend, platform, and infra engineering roles\.

## Location

Bengaluru

## AI stack

claude code

claude

cursor

gemini

opencode

claudecode

## Work experience

SDE 2 at Locus, Dec 2025 \- Present · 9 mos, Bengaluru, Karnataka, India, Working on core backend platform infrastructure, focused on reliability, observability, and data scalability across distributed microservices\. Key Contribution: • Drove org\-wide JDK 24 → 25 migration across 10\+ microservices via staged rollouts and compatibility gates, achieving zero\-downtime deployment with measurable runtime performance and maintainability gains\. • Re\-architected observability stack with OpenTelemetry — resolved cardinality explosion, fixed delta/cumulative temporality drift in Victoria Traces, and tuned sampling under 3× production load; cut monitoring cost without sacrificing signal fidelity\. • Engineered hot/cold data tiering retaining 1 year of records in hot storage via PostgreSQL partial indexes and pg\_cron; eliminated index bloat, enforced per\-tenant RBAC isolation, and improved high\-frequency query throughput significantly\. • Embedded Databricks analytics dashboards into the Locus platform with fully CI/CD\-driven provisioning via Databricks Asset Bundles and GitHub Actions — gave product teams self\-serve analytics and eliminated all manual deployment overhead\.

Machine Learning Engineer at Tekion Corp, Jul 2024 \- Nov 2025 · 1 yr 5 mos, Bengaluru, Karnataka, India, Part of the ML Platform team, building and scaling backend services that power real\-time LLM inference and AI\-driven CRM features\. Key Contributions: • Architected an event\-driven Kafka pipeline for real\-time ingestion of dealer\-customer call recordings — decoupled transcription, summarization, and intent\-extraction stages, enabling independent scaling and eliminating backpressure during burst traffic\. • Developed AI communication pipelines on Azure OpenAI to auto\-summarize call transcripts and generate personalized outreach emails; reduced email generation latency by 50% with per\-dealer prompt customization at scale\. • Established a Prompt Configuration Platform for LLM routing with per\-tenant quota enforcement and traffic shaping; maintained SLA adherence under high\-volume concurrent workloads without manual intervention\.

Software Engineer at tiket\.com, Jul 2022 \- Jul 2024 · 2 yrs 1 mo, Noida, Uttar Pradesh, India, Worked on the Post\-Order platform, owning microservices across multiple travel verticals including Flights, Hotels, Trains, Ferry, and more\. Key Contributions: • Owned end\-to\-end delivery of the Ferry Booking vertical — led system design, backend development, and cross\-team integration across payments, inventory, and notifications; shipped a net\-new booking line serving millions of users\. • Optimized Order Management APIs via query profiling, selective indexing, and caching — cut P95 latency by 50%; rebuilt Discount Engine Elasticsearch queries using filter context and reduced aggregation depth, dropping query volume by 50% and P99 latency by 40%\. • Engineered a Go microservice from scratch using Domain\-Driven Design \(bounded contexts\) for frontend APIs and CRM integrations; drove test coverage to 98% via SonarQube gates and delivered a plugin\-based Admin Dashboard 3\.0, cutting vertical onboarding time by 3×\. • Migrated microservices from Java to Golang, contributing to improved system performance and scalability; developed a custom Sentry integration library in Go for efficient error monitoring and observability across services\. • Integrated Grafana Hawkeye to monitor latencies across inbound and outbound microservice calls, improving system\-wide observability\.

## Education

Bachelor of Technology \- BTech, Information Technology, Bundelkhand Institute of Engineering and Technology, Jhansi

## Public links

- github: https://github\.com/shubham1908
- leetcode: https://leetcode\.com/gabbar9081
- codeforces: https://codeforces\.com/profile/shubh1908

[View the original profile](https://tal.club/meet/shubham-gupta-16)

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