GANESH.RAI

Systems Engineer

SYSTEM_INIT: Booting kernel...
STATUS: READY0%
Available for opportunity

Backend & Distributed Systems

Ganesh Rai

Architecting distributed services and high-performance system backends that scale with confidence.

ganesh@rai-systems: ~
Active Visualizer
API GATEWAY/schedule10K requests/sPartition 0Partition 1Partition 2KAFKA CLUSTERWORKER POOLUKG ReplicasJVM PerformanceCaffeine Cachep99 < 200 msRedisson LockDistributed LockPostgreSQLPersistent State
TPS Rate14,205
JVM Run14 ms
Partition12/12 Ok
StatusGreen
[$] ssh ganesh@rai.systems
[$] connecting to GCP-asia-south1...
[$] status: PIPELINE_ACTIVE
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Perspective

Systems built with intent.

About Me

Ganesh Rai

Backend Software Engineer with extensive experience building scalable microservices and distributed systems in Java, Spring Boot, and Kafka across GCP and Azure platforms. Adept at system design, event-driven architectures, JVM performance tuning, and backend platform engineering for enterprise-scale software applications.

I focus on eliminating native memory leaks, debugging pod memory footprints, configuring Kafka partitioning strategies, and holding latency below target metrics.

4+

Years of Focus

1M+

Active Devices

<200ms

p99 Local Cache

Hardware Setup

Workspace Engine

Display27" LG 4K UltraFine
KeyboardKeychron Q1 Pro (Brown Switches)
MouseLogitech MX Master 3S
Execution EngineJVM HotSpot (Memory Tuned: G1GC)
Platform Diagnostics Active
Capabilities
Hover to inspect version info

Backend Capabilities & System Tooling

Select or hover over any tech item below to see engineering specifics...
Java17 / 21
Spring Boot3.x
Apache KafkaEvent Streams
RedisRedisson Lock
Caffeine CachingIn-Memory
GCP / AzureCloud Infra
PostgreSQLv16
Docker / K8sContainers
Reading List

Notion Bookshelf

Designing Data-Intensive ApplicationsBy Martin Kleppmann
Java Concurrency in PracticeBy Brian Goetz
Clean ArchitectureBy Robert C. Martin
Updated Monthly
Interests

Hobbies & Quirks

☕ Specialty Coffee Brewing
🎮 Open-World RPG Gaming
📝 Technical Systems Blogging
🎧 Synthwave Playlists
Status: Active Learning
Metrics Monitoring

Production JVM Logs (Simulation)

[INFO] 2026-06-19 12:45:01 - JVM Memory Heap Usage: Init=512M, Max=4096M, Used=1254M. Active G1GC cycle clean.
[INFO] 2026-06-19 12:45:03 - Apache Kafka: Partition lag reports at 0 message packets across all 12 consumer topics.
[DEBUG] 2026-06-19 12:45:05 - Caffeine local cache hitting 94.2% queries. Spring ThreadPool active size: 14/50.
[INFO] 2026-06-19 12:45:08 - Stability state verified: REST endpoints checking at p95=42ms latency values.
Diagnostic Pipeline Connected
Capabilities

Technical Stack

languages

JavaSpring BootSpring MVCHibernateREST APIsJUnit 5Mockito

architecture

Distributed SystemsMicroservicesEvent-Driven ArchitectureApache Kafka

cloud

Google Cloud Platform (GCP)AzureDockerKubernetesSystems Design

databases

PostgreSQLMySQLRedisCaffeine CachingAsynchronous Processing

tools

DatadogGrafanaSplunkGitAgile/Scrum

core

JVM Memory ManagementPerformance TuningConcurrencyMultithreading
Showcase

System Architectures

A deep dive into high-performance backend platforms engineered with microservices, event-driven streams, and optimized caches.

Infrastructure & Platform Engineering

Event-Driven Distributed Task Scheduler

Engineered a high-throughput, fault-tolerant distributed task scheduling and dispatch engine processing high-frequency enterprise operations with guaranteed order delivery.

Java
Spring Boot
Apache Kafka
Redis
Docker
GCP
Migrated queue polling models to partition-aware event streams, slashing peak system latency by 35%.
Implemented distributed locking using Redisson to prevent race conditions and duplicate task executions across horizontal replicas.
Active Partition FlowAPI IngestPart 0Part 1Part 2Workers
PEAK LATENCY REDUCTION-35%
STABILITY RATING99.99%
Distributed Systems & Diagnostics

Real-Time Device Telemetry Aggregator

Developed a telemetry processing pipeline cataloging logs, heartbeat pings, and remote diagnostics for 1M+ active IoT router configurations.

Diagnostics PipelineIoTKafkaCaff
Java
Spring Boot
Apache Kafka
PostgreSQL
SCALABILITY RATE1M+ Routers
DB OPTIMIZATION60% Reduction
Platform & Data Engineering

Optimized Enterprise Metadata Catalog

Designed a secure inventory catalog system tracking ownership, data lineage, and schemas for 200+ relational and transactional data stores.

Inventory Mapping200+ StoresLineage State
Java
Spring Boot
PostgreSQL
REST APIs
METADATA STORES200+ Stores
LINEAGE ACCURACY+30%
Infrastructure & Buffer Engineering

High-Throughput Log Pipeline Buffer

Engineered a distributed log buffer service handling high-throughput ingress streams, using Redis stream buffers to prevent database ingestion spikes.

Stream Buffer IngressAPIRedisStrm
Java
Spring Boot
Redis Streams
Docker
INGESTION BUCKET50K logs/s
DB COOLDOWN40% Saved
Concurrency & State Management

Distributed Transaction Ledger Lock

Developed a distributed transaction ledger lock manager validating consensus state transitions across active read-write partitions with zero data drift.

Consensus VerificationConsns
Java
Spring Boot
Apache Kafka
PostgreSQL
CONSENSUS NODES5 Replicas
STATE DRIFT0.00%
Trajectory

Professional Journey

Software Engineer II

Ultimate Kronos Group (UKG)
04/2025 - PresentNoida, India
Migrated a CPU-intensive scheduling workflow to an event-driven architecture using Apache Kafka on GCP, reducing peak-hour response times by 35% across 10,000+ daily enterprise scheduling requests.
Led incident response for recurring Kubernetes OOM pod crashes across a Java 17 migration, isolating native memory leaks and JVM heap misconfiguration via heap-dump and GC-log analysis, and restoring production stability within 48 hours while unblocking 5 dependent teams.
Slashed p95 API latency by 25% and boosted throughput by 40% via JVM thread-contention profiling, Spring Boot hot-path re-engineering, and blocking I/O elimination — confirmed through Datadog APM monitoring across 3 high-traffic endpoints.
Deployed Caffeine in-memory caching for high-frequency shift-query APIs, cutting database round-trips by 60% and holding p99 latency-critical response times below 200 ms during peak-load spikes.
Coached 2 junior engineers on JVM diagnostics, JUnit-based test automation, and Datadog observability, shrinking mean on-call incident resolution time by 25% through structured mentorship.

Software Engineer

Jio Platforms Limited
07/2022 - 03/2025Mumbai, India
Built REST APIs on Azure using Spring Boot and PostgreSQL for a clinical annotation platform serving 50+ concurrent clinicians, adding versioning and consensus workflows that lifted ML dataset quality by 20%.
Delivered a Data Dictionary service on Azure to catalogue ownership, lineage, and quality metrics across 200+ data assets, raising data accuracy by 30% and trimming cross-team approval cycles by 40%.
Extended the Service Quality Monitoring platform with remote WiFi router diagnostics spanning 1M+ deployed devices, enabling proactive fault detection that dropped field-engineer dispatches by 25% and repair costs by 20%.
Connectivity

Let's build the systems of tomorrow.

Whether you want to discuss JVM memory tuning, Apache Kafka stream architectures, container deployments, or scale backends, my inbox is always open.

Email Addressganeshrai.work@gmail.com Click to copy
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GitHubgithub.com/gaxraiView repository sources