Software Engineer II/Amazon/Seattle

Nishanth Bysani

I build platforms other teams build on. This desk holds a few of my favourite things. Pick one up.

(About)

A little about me

I’m a software engineer at Amazon in Seattle with 6+ years of building distributed systems. I’m drawn to the hard middle of engineering: platforms that many teams depend on, services that have to stay up at peak, and tools that make other engineers faster.

Recently that’s meant a shared platform that saves about 34 engineering weeks for every product built on it, a GenAI code generator that cut new-service build time from 8 weeks to 3, and readiness work that kept a checkout platform steady at 200K+ requests a second. Before Amazon, I built banking and insurance software in Hyderabad and earned an MS in Computer Science from UT Arlington with a 4.0.

Outside work, I play snooker and pool, read a lot of manga (big Naruto and One Piece fan), and I’m working on being more active.

  • 6+ years in distributed systems
  • Seattle, WA
  • MS CS, UT Arlington (4.0)
Favourite book Anxious People Fredrik Backman
On repeat Marea (we’ve lost dancing) Fred again.., plus The Nights · Avicii
Favourite place Hawaiʻi, July 2025
Best night out Coldplay, Sept 20, 2023 Runner-up: the Northern Lights over Seattle
Favourite shortcut ⇧⌘Space Speech to text
Right now learning to build agentic systems
Favourite book
Anxious People
Fredrik Backman
Fiction
On repeat
Marea(we’ve lost dancing)
Fred again..
Favourite place
Palm trees silhouetted against an orange sunset over the ocean in Hawaiʻi

Hawaiʻi, July 2025

Right now
Currentlylearning to build agentic systems
Best night out
Admit oneColdplaySept 20, 2023
No. 0920
Favourite shortcut
⇧⌘Space
Click to copy
Nishanth Bysani
Software Engineer II
Say hello
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(Experience) · 2016–now

Where I’ve worked

Scroll or hover through the roles, and the badge keeps up. Open one to see what I built there.

  1. 2022
    Amazon · Credit products
    One bank-account platform instead of one per product. Read the story ↓
    Amazon · Developer productivity
    New payment services in 3 weeks, not 8. Read the story ↓
    Amazon One · Payment tokenization
    Moved palm payments to AWS without anyone noticing. Read the story ↓
    PayStation · North America checkout
    Checkout that holds at 200K requests a second. Read the story ↓
    200K+Requests a second at peak
  2. 2021
    QueryGrid · GCP connector
    Query BigQuery from Teradata without moving the data.

    I designed and built the GCP connector for Teradata QueryGrid, so customers can run federated analytics across Teradata Vantage, BigQuery and Google Cloud Storage in place, instead of migrating data first. Built with GCP engineering, Teradata's optimizer teams and Fortune 100 customers.

    ~80% Less integration effort for enterprise customers
    80%Less customer onboarding effort
  3. 2020

    Coursework: Algorithms, Cloud, NLP, Machine Learning.

    4.0GPA out of 4.0
  4. 2019
    Supply chain automation
    Invoices in, trucks out.

    An orchestration system that reads invoices from Salesforce CRM, checks real-time product availability, and triggers truck dispatch automatically, cutting manual coordination and fulfilment delays.

    Document intelligence
    Insurance fine print, read automatically.

    A claims-processing pipeline that uses spaCy and BERT to extract, normalise and standardise policy terms, so claims teams spend less time reading documents and more time paying out.

    ~35% More efficient claims disbursement team
    35%More efficient claims team
  5. 2016
    Banking · Card issuance
    Five systems, one card, a fraction of the wait.

    An automated card issuance system for a multinational bank that ties five separate systems together over REST, with real-time credit history checks along the way.

    80% Faster card issuance turnaround
    Banking · Lead generation
    3,000 new clients in two months.

    A lead management system that pulls public data from the Central Bank of the UAE and turns it into reports on commercial entities, giving the bank's sales team a ready-made pipeline.

    3,000+ New clients in two months
    80%Faster card issuance
(Projects) · Amazon, 2022–now

Things I’ve built

Four pieces of my work at Amazon. The drawings are simplified. The numbers are real.

CREDIT PRODUCT 1CREDIT PRODUCT 2CREDIT PRODUCT 3SHAREDONBOARDING+ PAYMENTSBANK ACCOUNT~34 engineering weeks saved per product
Amazon · Credit products

One bank-account platform instead of one per product.

Each credit product was building its own bank-account onboarding and payment flow. I architected a shared servicing platform they can all plug into, so a new product reuses one integration instead of rebuilding it.

~34
Engineering weeks saved per product
$15M
Projected business value
  • Java
  • AWS
  • DynamoDB
SPECPROMPT CHAIN123REASON · PLAN · WRITE// API// ORCHESTRATIONBUILD TIME PER SERVICE~8 WKS~3 WKS
Amazon · Developer productivity

New payment services in 3 weeks, not 8.

I built a GenAI code generator that chains prompts and step-by-step reasoning to write the API and orchestration layers of a new microservice. Teams start from a standard, working service instead of a blank repo.

~3 wks
To build a new service
4
Tier-1 payment services built this way
  • Amazon Bedrock
  • Prompt chaining
  • Java
AMAZON ONETOKENLEGACYRETIREDAWS-NATIVECARDNETWORKZero-impact cutover
Amazon One · Payment tokenization

Moved palm payments to AWS without anyone noticing.

Amazon One lets people pay with their palm. I helped move the card-network tokenization services behind it to an AWS-native architecture with the card networks and platform teams, then switched traffic over and retired the old infrastructure.

0
Customer impact at cutover
3.2–3.7s
Latency held under peak load
  • AWS
  • Java
  • Card networks
INCOMINGVIPPARTITION 1PARTITION 2PARTITION 3CONTAINEDPARTITION 4200K+ requests a second at peak
PayStation · North America checkout

Checkout that holds at 200K requests a second.

Before global retail peaks, I drove the scalability work on PayStation: splitting traffic with VIP partitioning and adding resilience so one bad partition can't take the others down with it.

200K+
Requests a second at global retail peak
  • AWS
  • VIP partitioning
  • Resilience
(Contact)
Let’s talk

Working on hard scaling problems, or building with GenAI? I’m always up for comparing notes.

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