Java backend · distributed systems · production engineering

I build backend systems that stay correct under load and failure.

Software Engineer with 4+ years across fraud screening, financial workflows and integration systems. I build services, tune hot paths, reason about transaction boundaries, and stay close enough to production to understand how the system actually fails.

Performance−40% p95

JFR-guided work across Hibernate access patterns, SQL, composite indexes, HikariCP and Redis caching.

production
Throughput+15%

Improved backend throughput after service, persistence and cache-path optimization.

production
Reliability99.8% uptime

Supported with CloudWatch, structured logging, alerting, runbooks, incident triage and RCA-driven fixes.

production
Operations35 → 12 min

Reduced MTTR by strengthening failure isolation, debugging paths and operational playbooks.

production
02 / Public systems

Public systems with inspectable code, tests and engineering constraints.

Each entry points to code a reviewer can inspect. Vortex is the flagship systems project; the remaining repositories show distributed-systems, Java, AI-tooling and MLOps breadth.

GPU systems · public

Vortex CUDA

An exact vector-search engine built from CUDA kernels through C++20, Java JNI and a Spring Boot API. The system keeps indexes resident on the GPU, supports FP16 storage with FP32 accumulation, and includes a reproducible benchmark harness instead of relying on one-off timing claims.

CUDA · C++20 · JNI · Java 17 · Spring Boot · exact Top-K · FP16
16.7×lower P50 vs project scalar CPU reference
1.67–1.72 msFP32 P50 · 500K × 128 · Top-10
1.64K+FP32 QPS · batch 32
50%vector-storage reduction with FP16
04 / Career record

From backend delivery to production ownership.

The progression below focuses on systems shipped, production responsibility and measurable engineering outcomes.

APR 2025 — NOW

Linux Socials

Software Engineer

Designed and owned fraud-screening backend services, tuned latency and throughput, hardened dependency behavior, and supported production through observability, incident response, runbooks and RCA.

DEC 2021 — APR 2024

Merkle Inspire Pvt Ltd

Associate Software Engineer

Built Java/Spring financial microservices, transaction workflows and an external-data job portal; supported three production microservices and improved release velocity through testing, CI, reviews and cross-functional delivery.

JUN 2021 — NOV 2021

Merkle Inspire Pvt Ltd

Technical Intern

Implemented backend/API components and reduced query execution time by 27% through SQL rewrites and index tuning while building testing and database-performance fundamentals.

05 / Engineering surface

Engineering depth I can defend.

Concrete examples from production work and public systems across service design, data consistency, distributed behavior and operations.

Service design

Java · Spring Boot · Spring MVC · REST APIs · JPA/Hibernate · validation · exception handling · service boundaries

Data & consistency

MySQL · PostgreSQL · Redis · SQL tuning · composite indexes · transaction management · isolation · optimistic locking

Distributed behavior

Kafka · idempotency · retries · timeouts · circuit breakers · rate limiting · asynchronous processing · concurrency

Production

AWS · EKS · Docker · Kubernetes · Jenkins · CloudWatch · structured logging · alerting · runbooks · RCA · JFR

06 / Contact

Backend systems. Measurable behavior. Fewer surprises in production.

Open to backend and software-engineering roles where system design, performance and operational ownership matter.