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Amulya Kashyap

@amulyakashyap

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Computer Scientist at Adobe who re-architected Webpages publishing to support growth from 1M to 1.35M MAU.

India

Message

At Adobe, I re-architected the Webpages publishing pipeline, removing a throughput bottleneck and enabling platform growth from 1M to 1.35M MAU. I also built Python FastAPI services for internal AI workflows and deployed Elasticsearch indexing that achieved under 200ms p95 latency.

At Paytm, I built Wallet Payment Services REST APIs supporting 10M+ MAU and designed a RabbitMQ messaging system delivering 500K+ notifications a day. Earlier, I designed microservices APIs at IndusOS for a distributed system serving 100M+ users and launched site-wide search with the ELK Stack.

Experience

Work history, roles, and key accomplishments

Current

Computer Scientist

Current

Adobe

May 2022 - Present (4 years 5 months)

Re-architected the Webpages publishing pipeline to unblock platform growth from 1M to 1.35M MAU. Built internal AI workflow services using Python FastAPI, reducing integration turnaround time by ~20%.

NodeJS Go Python fastAPI Kubernetes Docker Helm Jenkins TypeScript React LLM APIs RAG Elasticsearch DynamoDB ELK Stack

Senior Software Engineer

Paytm

Feb 2021 - May 2022 (1 year 3 months)

Built Wallet Payment Services REST APIs from scratch, supporting 10M+ MAU with 99.95% uptime. Migrated legacy .NET services to Node.js and FastAPI-based microservices, improving onboarding speed by 50%.

NodeJS Go Python fastAPI Kubernetes Docker Helm MongoDB Elasticsearch RabbitMQ

Senior Backend Developer

IndusOS

Oct 2018 - Feb 2021 (2 years 4 months)

Designed microservices APIs for a distributed system serving 100M+ users, maintaining 99.9% SLA. Launched site-wide search with ELK Stack, increasing average session duration by 93%.

NodeJS Python fastAPI Kubernetes MongoDB New Relic ELK Stack

Senior Software Engineer

BookMyShow

May 2018 - Oct 2018 (5 months)

Integrated WhatsApp messaging at scale, raising delivery rate by 25-35% and reducing communication costs by ~30%. Optimized legacy system and migrated code to Golang, improving API response times by 20-30%.

Go MongoDB New Relic ELK Stack

Backend Developer

Clicklabs / Jugnoo

Jan 2016 - May 2018 (2 years 4 months)

Developed real-time ride tracking APIs utilizing WebSockets for 10K-20K concurrent sessions, increasing responsiveness by ~40%. Standardized system observability with the ELK Stack, reducing MTTD by ~50%.

NodeJS MongoDB RabbitMQ ELK Stack