Karan Pahlani

Karan Pahlani

Software Engineer passionate about building scalable solutions and creating meaningful impact.

SOFTWARE
ENGINEER

Senior Software Engineer & Technical Leader who scaled Fetch Rewards from 1M to 12M+ monthly active users. Architected resilient systems handling 80K+ RPS, led engineering pods, and delivered $30K monthly cost savings through innovative solutions.

6+
YEARS OF
EXPERIENCE
12M
MONTHLY
ACTIVE USERS
80M
WEEKLY
RECEIPTS

๐Ÿˆ SUPER BOWL IMPACT

Led the technical transformation that enabled Fetch Rewards to handle unprecedented Super Bowl ad traffic surge while maintaining zero downtime and delivering seamless user experience.

13x
TRAFFIC SURGE HANDLED
6K RPS โ†’ 80K RPS

๐ŸŽฏ Lead Architect Role

  • โ€ข Built resilience using Kafka & SQS replay mechanisms
  • โ€ข Transformed synchronous to asynchronous processing
  • โ€ข Orchestrated infrastructure scaling pre/post event
  • โ€ข Provided real-time monitoring & incident response
0
MINUTES DOWNTIME
During peak traffic

โšก Technical Innovation

  • โ€ข Months of preparation & system optimization
  • โ€ข Email & direct receipt integration scaling during ad
  • โ€ข Provider connectivity (Amazon, Gmail, Target, Walmart)
  • โ€ข Performance monitoring during live event

๐Ÿงพ DIGIDETECTOR PLATFORM

Engineered ML-powered receipt processing platform serving millions of users with industry-leading accuracy and scale.

97%
ACCURACY RATE
80M
WEEKLY RECEIPTS
100x
DUPLICATE BLOCKING
99.99%
SLA MAINTAINED

๐ŸŽฏ Technical Architecture

  • โ€ข AWS SageMaker ML models for item identification
  • โ€ข Python microservices for receipt processing
  • โ€ข Go microservices for high-performance APIs
  • โ€ข Email integration (Gmail, Outlook, Yahoo)
  • โ€ข Direct retailer APIs (Amazon, Walmart, Target)

๐Ÿš€ Business Impact

  • โ€ข 97% accuracy in item identification
  • โ€ข Processing 80M+ receipts weekly
  • โ€ข 100x improvement in duplicate detection
  • โ€ข Maintained 99.99% reliability SLA
  • โ€ข Enabled platform scaling to 12M+ MAU

ABOUT

Technical Leader & Senior Software Engineer who scaled consumer platforms from 1M to 12M+ monthly active users. Led engineering pods, mentored junior developers, and drove the architectural evolution from Java/MongoDB monoliths to distributed Go microservices.

๐Ÿ’ป Core Technologies

Backend:Go, Java, Python, Node.js, Ruby on Rails
Frontend:React, TypeScript, JavaScript
APIs:REST, gRPC, GraphQL

โ˜๏ธ Infrastructure & Data

Cloud:AWS (SQS, S3, SageMaker), Docker, Kubernetes
Databases:PostgreSQL, DynamoDB, MongoDB, Redis
Messaging:Kafka, AWS SQS, Event-Driven Architecture

๐Ÿ‘ฅ Leadership & Impact

Led small engineering pods and drove cross-team initiatives, mentoring junior engineers and setting coding/design standards. Focused on setting clear goals, building trust, and empowering engineers to take ownership rather than micromanaging.

$30K
Monthly Savings Achieved
1Mโ†’12M
User Growth Enabled
5+
Engineers Mentored

WORK

EXPERIENCE

Fetch Rewards

5 Years of Professional Growth โ€ข July 2020 - Present

fetch.com โ†—
80K+
RPS Handled
$30K
Monthly Savings
90%
Faster Integration
1Mโ†’12M
Users Scaled

๐Ÿˆ Super Bowl Traffic Resilience

Led architectural transformation from synchronous to asynchronous receipt processing during Fetch's Super Bowl ad campaign. Built resilient distributed system using Kafka & SQS replay mechanisms to handle 13x traffic surge (6,000 RPS โ†’ 80K RPS).

๐Ÿš€ Impact:

13x traffic scaling during Super Bowl ad, Zero downtime, Real-time incident response

GoKafkaAWS SQSDynamoDBReal-time Monitoring

๐Ÿงพ eReceipts DigiDetector Platform

Architected ML-powered receipt processing platform handling 80M+ weekly receipts from Amazon, Walmart, Target, Gmail, Outlook. Built Python microservices with SageMaker ML models achieving 97% item identification accuracy.

๐Ÿš€ Impact:

97% accuracy, 80M+ weekly receipts, 100x duplicate blocking improvement, 99.99% SLA

PythonAWS SageMakerGo MicroservicesML ModelsEmail Integration

๐Ÿค Self-Service Partner Platform

business.fetch.com โ†—
๐Ÿข Enterprise Partners
PepsiKimberly ClarkUnilever+17 More

Architected business.fetch.com - a comprehensive B2B platform enabling major CPGs (Pepsi, Kimberly Clark, Unilever) to self-service campaigns. Built plug-and-play Go microservice for external IDPs (Okta, PingID) with real-time Grafana monitoring.

2x
Pepsi Ad Spend Increase
20+
External IDP Integrations

๐ŸŽฏ Impact: 20+ enterprise partners onboarded, Pepsi doubled ad spend, 90% faster integration

GoOIDC/SAMLOkta/PingIDReactGrafanaPostgreSQL

๐Ÿ“‹ Universal Product Catalog

Millions
Products Catalogued
Real-time
Updates & Ingestion
FIDO
Unique ID System
๐Ÿ”ง Technical Innovation
  • โ€ข Multi-source ingestion (XLSX, CSV, web scraping)
  • โ€ข Fuzzy matching algorithms for product identification
  • โ€ข ML-powered deduplication & consolidation
  • โ€ข FIDO system solving UPC length/format issues
๐Ÿ“Š Business Impact
  • โ€ข 35% improvement in receipt-to-product matching
  • โ€ข 60% faster partner data processing pipeline
  • โ€ข 20% user engagement boost via search/recommendations
  • โ€ข Enhanced partner confidence & reporting accuracy
  • โ€ข Direct revenue increase through better matching

๐ŸŽฏ Results: 35% better receipt matching, 60% faster processing, 20% user engagement boost, revenue increase

GoJava Spring BootPostgreSQLDynamoDBFuzzy MatchingWeb Scraping

๐ŸŽ† Consumer-First Engineering Excellence

๐Ÿ‘ฅ Consumer Impact
  • โ€ข Scaled platform from 1M โ†’ 12M monthly active users
  • โ€ข Processed 80M+ receipts weekly with 99.99% reliability
  • โ€ข Enabled seamless receipt scanning during Super Bowl
  • โ€ข Delivered 97% accuracy in receipt item identification
๐Ÿ”ง Technical Excellence
  • โ€ข Monolith โ†’ Microservices transformation
  • โ€ข Event-driven architecture with Kafka & SQS
  • โ€ข ML-powered processing with AWS SageMaker
  • โ€ข Multi-provider integrations (Amazon, Gmail, Target)
Go MicroservicesAWS SageMakerKafka + SQSPython MLReceipt ProcessingPartner APIs

๐Ÿ’ผ Previous Experience & Innovation

๐Ÿค– Resume Scraping & Scoring Tool
Edammo Inc

Built a full-stack resume scraping and scoring tool that automated candidate sourcing for recruitment processes.

๐Ÿš€ Business Impact: 40% reduction in initial screening time

ReactNode.jsMachine LearningWeb Scraping
๐Ÿ“ˆ Career Trajectory

Progressed from building recruitment automation tools to leading large-scale consumer platforms. Consistently delivered measurable business impact through technical innovation and leadership.

Get In Touch

Let's build something amazing together. Open to Senior Engineer, Staff Engineer, and Technical Leadership roles.

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ยฉ 2024 Karan Pahlani

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