---
title: "Shivendra Pratap Singh - SDE L5 in Bengaluru | Tal"
description: "Meet Shivendra Pratap Singh, SDE L5 at Amazon | Backend Engineering | VIT 2019 | Java and Python | DSA | System Design | Fullstack Developer based in Bengaluru. AI stack includes anthropic apis, claude, and hugging face. Explore public work links including linkedin.com."
image: "https://tal.club/meet/shivendra-pratap-singh-3/share-image"
---

# Shivendra Pratap Singh on Tal

## Headline

SDE L5 at Amazon \| Backend Engineering \| VIT 2019 \| Java and Python \| DSA \| System Design \| Fullstack Developer

## About

• Building Amazon's cross\-border architecture that lets customers shop across borders on Amazon: Global Store arcs, Bazaar and Haul apps, and external partner integrations like JD\.com, Kettle, and 11st\. • Interested in building large\-scale distributed systems, algorithmic problem\-solving, and lately, making production systems consumable by AI agents \(MCP, agentic workflows\)\. • Experienced across backend, data infrastructure, and cloud: Java, Python, TypeScript, Go, JavaScript, Ruby on Rails, SQL, React\. • Comfortable with the AWS toolbox: CDK, Lambda, Kinesis, DynamoDB, S3, SNS, IAM, CloudWatch\. • Also worked plenty with Kafka, Redis, Elasticsearch, PostgreSQL, MongoDB, Docker, and Git along the way\. • Love sports, and TV shows that have good storylines\. • Love exploring new places and meeting new people\. • Can't live without friends and family\. • I am a most\-active\-when\-it's\-2:30\-in\-the\-night person\. • Want to be the hero who saves the world\.

## Location

Bengaluru

## AI stack

anthropic apis

claude

hugging face

kiro

Amazon Q Developer

JetBrains AI Assistant

## Work experience

SDE L5 at Amazon, Aug 2025 \- Present · 1 yr 3 mos, Bangalore Urban, Karnataka, India, CrossBorder \| Platform Infrastructure, Global Store Core, Search • Lead technical direction for a 15\-engineer team across 4 CrossBorder workstreams \(platform infrastructure and gateway, Global Store Core, Search, and Security/Compliance/Privacy\), owning roadmap, engineering guidelines, growth, delivery, and operations end to end\. • Led the Amazon\-JD\.com integration enabling all US and JP marketplace use cases\. Designed and built the multi\-marketplace platform layer \(credential routing, per\-marketplace secrets, webhook source identification, event orchestration\) and drove adoption across 24 downstream teams through launch campaign\. The integration now handles $2\.1M\+ in weekly order sales, about $110M a year\. • Author or peer\-review roughly one system design a week and mentor engineers across the team\. • Cut p90 checkout latency of Global Store orders by \~78% by parallelizing line\-item processing that previously ran sequentially, without breaking correctness of the shared order document model\. • Shipped the Repay feature for cross\-border payments so customers can retry failed payments, this eliminated 60% of order failures caused by payment declines\. • Wrote reusable AWS CDK constructs \(KinesisFirehoseToS3Construct, S3ReplicationSourceConstruct\) for general\-purpose cross\-partition data replication, adopted by other teams with minimal configuration\. Everything ships through automated CI/CD with metrics, alarms, and dashboards\. • Built MCP servers over Global Store ordering services and integrated the gateway with production ordering APIs, making core ordering systems directly consumable by AI agents on internal AI\-native platforms\. Tech Stack: Java, TypeScript, AWS CDK, Lambda, ECS, Kinesis Data Firehose, S3, DynamoDB Streams, SQS, SNS, Secrets Manager, IAM, MCP, Spark\-based ETL \(Cradle\), SQL, CI/CD

Senior Software Engineer at Zeta Global, Mar 2024 \- Jul 2024 · 4 mo, India, Audience Explorer \| Estimator Service \| Segmentation • Owned and re\-architected the Estimator Service, a core backend system that returns real\-time audience size estimates for complex, nested segmentation filters over 2 Billion user profiles\. • Designed a hybrid two\-tier estimator: a fast path on bitmap indexes and HLL approximate cardinality, with a fallback slow path using progressive SQL planning for long\-tail filters\. • p99 latency went from 11s to \~700ms and p50 from 2\.5s to \~300ms\. The demo helped win a key enterprise client\. • Led cross\-functional work with Product, Data Science, and DevOps to define estimation SLAs, tune Snowflake and PostgreSQL performance, and keep accuracy tolerances aligned with the product\. • Authored the system architecture documentation for Audience Explorer services covering service interactions, data flows, and failure points\. Onboarding and debugging got 50% faster\. • Cut User Exploration query latency by 60% with Snowflake materialized views, batch precomputation in Python, and better PostgreSQL indexing, enabling dynamic real\-time analysis\. Tech Stack: Java, Python, Ruby on Rails, JavaScript, Kafka, Redis, AWS, PostgreSQL, Snowflake, React, Unix

SDE II at Tata 1mg, Aug 2023 \- Mar 2024 · 8 mos, Gurugram, Haryana, India, Search Service \| Latency, Caching, and Relevance • Worked with the Merchandising team on the product search service used by millions of users across web and mobile\. • Rewrote Elasticsearch queries with inverted indexing and removed redundant aggregations: p99 dropped 60% \(\~2200ms to \~880ms\) and p50 45% \(\~800ms to \~450ms\)\. • Added Redis caching for frequently accessed queries; cache hit rate rose 35% and Elasticsearch query volume fell 40%\. • Fed user context \(past purchases, clickstream behavior\) into ranking with Elasticsearch boosting and custom scoring\. Search\-to\-purchase conversion went up 17%\. • Search query failures dropped 71%, holding reliability under peak traffic\. Tech Stack: Python, Java, Ruby on Rails, JavaScript, Redis, Kafka, Elasticsearch, PostgreSQL, MongoDB, Sanic, React, Unix

Software Engineer at CleverTap, Oct 2021 \- Nov 2022 · 1 yr 2 mos, Mumbai, Maharashtra, India, Partner Integrations \| API Security \| Large\-Scale Data Export • Built and scaled the partner export system handling terabyte\-scale data exports to AWS S3, Amplitude, Segment, Mixpanel, mParticle, and others\. • Redesigned the export pipeline around chunk\-based processing with MongoDB cursor pagination, Kafka job queues, and Redis\-backed caching, so failed chunks retry independently instead of failing the whole export\. • Parallelized exports with Java thread pools and distributed worker pools: export time fell from \~5 hours to \~30 minutes at 10x throughput on the same infrastructure\. • Owned and delivered multiple partner integration features: Multiple Passcode \(header\-based authentication for all Consumption APIs\), the Mixpanel Import Deletion Layer \(recurring and one\-off cohort cleanups\), and the Segment Destination Integration \(CleverTap as a supported destination on Twilio Segment\)\. Tech Stack: Java, Python, JavaScript, Kafka, Redis, AWS, MongoDB, PostgreSQL, Apache Struts, Vue\.js

Developer Associate at SAP Labs India, Jan 2020 \- Sep 2021 · 1 yr 9 mos, Bangalore, SAP SuccessFactors \| Enterprise Benefits Management • Worked in the Benefits team \(Globalization Services\) on core modules: Insurance, Pension, Savings Plans, Allowances, and Reimbursements for global enterprise clients\. • Built a metadata\-driven benefits configuration system on the SAP MetaData Framework \(MDF\) that lets HR teams define country\-specific rules without code changes, cutting custom development effort by 70%\. • Led design and rollout of a UK\-specific pension scheme: a decorator/wrapper architecture injected region\-specific logic into legacy systems without touching core pension flows, with feature\-flagged tenant rollout and full backward compatibility\. Other geographies later reused the pattern\. • Delivered UI enhancements in SAP UI5, optimized OData REST APIs, and added lazy loading; benefits selection page load times dropped 30%\. Tech Stack: Java, Python, JavaScript, Spring, MDF, SAP UI5, SAP Cloud, Redis, Jenkins, Unix

Senior Tech Associate at Bank of America, Jun 2019 \- Jan 2020 · 7 mo, Chennai

## Education

Bachelor of Technology, minor in Computer Science, Vellore Institute of Technology

Software Development, Problem Solving and System Design, Scaler

## Public links

- linkedin\.com: https://www\.linkedin\.com/in/shivendrasinghprofile

[View the original profile](https://tal.club/meet/shivendra-pratap-singh-3)

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