SYS.MOD // MAINFRAME → CLOUD

Suyog Bachhav

Software Engineer — Backend & AI

Backend engineer at AWS building high-throughput distributed systems — and applying agentic AI to modernize them.

View Projects Download Resume Contact Me

// ABOUT

About

I'm a software engineer at Amazon Web Services in Dallas, where I work on large-scale legacy modernization — transforming millions of lines of mainframe code into cloud-native Java microservices for enterprise clients in insurance and fintech.

My specialty is the hard part of modernization: zero-downtime data migrations, transactional consistency across heterogeneous data layers, and performance at scale — systems processing tens of thousands of transactions a day at sub-200ms P99 latency.

Increasingly, my work sits at the intersection of backend engineering and AI: I use agentic AI tooling (AWS Transform, Amazon Kiro) in production modernization workflows, and I'm actively building AI engineering projects to push further in that direction.

Before AWS, I built full-stack business systems at Mass Technologies in India, and I hold a Master's in Computer Science from Illinois Institute of Technology, Chicago.

// EXPERIENCE

Experience

Software Development Engineer · Amazon Web Services

Dec 2023 — Present

Dallas, TX

State Farm ECS

Spring Boot · PostgreSQL · Redis · AWS SES · AWS M2 · Atomikos

Modernized 5M+ lines of mainframe code into Java microservices using AWS Transform's agentic AI service, maintaining end-to-end functional equivalence.
Achieved zero-downtime migration of 15M insurance claims from DB2 z/OS to PostgreSQL Aurora — processing 50K daily transactions at <200ms P99 latency — by architecting a dynamic data-source routing framework with JTA transaction management and XA/non-XA support.
Sustained 2.4M+ daily stored-procedure invocations under a sub-800ms SLA by building hybrid REST microservices that replaced legacy mainframe calls with Spring Boot orchestration.
Improved email delivery reliability to 99.9% by replacing the legacy Exchange-based mail service with an AWS SES-integrated utility (automated domain verification, TLS via AWS SDK v2).

FIS Omni

Spring Boot · PostgreSQL · S3 · M2 · BluInsight · JProfiler

Reduced manual engineering overhead by ~40% across 10+ microservices by integrating Amazon Kiro (AWS's agentic AI IDE) for spec generation, automated documentation, and performance bottleneck analysis.
Improved batch job execution from 14 minutes to under 1 minute (>90% throughput gain) by engineering a multithreaded message-processing system that parallelized XML generation and MQ publishing.
Cut manual configuration overhead by 50% by centralizing YAML-based configuration merged with AWS Secrets Manager, with schema- and step-level data-source granularity.

Software Engineer · Mass Technologies

Jun 2019 — Aug 2021

India

Inventory Insight System

React.js · Spring Boot · PostgreSQL · JUnit

Built an AWS-hosted inventory management system on Spring Boot and PostgreSQL that streamlined product-quantity tracking for Purchase and Finance departments.
Designed RESTful APIs and a dynamic React.js interface with reusable components for real-time inventory tracking and CRUD operations.
Implemented role-based access control with Spring Security, restricting data visibility by user role for compliance.

// SKILLS

Skills

Languages

Java
Python
TypeScript
JavaScript
C++
SQL

Backend & Frameworks

Spring Boot
Hibernate
JUnit
React
Next.js
Tailwind CSS

AI Engineering

AWS Transform (agentic modernization)
Amazon Kiro (agentic IDE)

Data & Infrastructure

PostgreSQL (Aurora)
Redis
Docker
Jenkins
Git
Postman

Cloud (AWS)

SES
S3
M2
Secrets Manager
Aurora

// PROJECTS

Featured Projects

Case Study · AWS

Professional work · no public repo

State Farm ECS — Mainframe → Cloud Modernization

Problem

A major insurer's claims platform ran on DB2 z/OS mainframe — expensive, hard to change, and risky to migrate with business running on it.

What I built

A dynamic data-source routing framework with JTA/XA transaction management enabling zero-downtime migration; hybrid REST microservices replacing mainframe stored-procedure calls; AWS SES mail integration.

15M

claims migrated

<200ms

P99 latency

50K

daily transactions

5M+

lines modernized with AI

Java
Spring Boot
PostgreSQL Aurora
Redis
AWS M2
AWS SES
Atomikos
AWS Transform

Case Study · AWS

Professional work · no public repo

FIS Omni — Batch Modernization & AI-Assisted Engineering

Problem

Legacy batch pipelines took 14 minutes per run, and engineering overhead across 10+ microservices slowed the modernization program.

What I built

A multithreaded message-processing system parallelizing XML generation and MQ publishing; centralized YAML + Secrets Manager configuration; Amazon Kiro integration for spec generation and bottleneck analysis.

14min → <1min

batch execution time

~40%

less engineering overhead

50%

less config overhead

Java
Spring Boot
PostgreSQL
S3
AWS M2
BluInsight
JProfiler
Amazon Kiro

Personal Project

HealthHub — Healthcare Discovery & Appointments Platform

Full-stack healthcare platform: register, find nearby doctors, hospitals, and pharmacies, book appointments, and browse Yelp-sourced reviews with rating visualizations and Google Maps integration. Elasticsearch powers search with autocomplete.

Angular
Spring Boot
Elasticsearch
MySQL
MongoDB
Yelp API
Google Maps API

GitHub ↗

Personal Project

Distributed Sort — Hadoop vs. Spark

Implemented and benchmarked large-scale distributed sorting on Hadoop MapReduce and Apache Spark clusters, with automated build/run scripts against gensort-generated datasets on HDFS and a written performance report. Team project of three.