Hi, I'm V
Systems & AI Infrastructure Engineer building distributed backends, production-grade RAG pipelines, and real-time embedded systems.
VH

About

Systems-focused Software Engineer specializing in distributed architectures, LLM infrastructure, and real-time embedded systems. Experienced in architecting hybrid RAG pipelines, event-driven Kafka backends, cloud-native microservices, and multithreaded real-time systems with strong emphasis on reliability, observability, and performance.

Work Experience

Skills

C++
Go
Python
Java
PostgreSQL
Docker
Kubernetes
My Projects

Check out my latest work

I've worked on a variety of projects, from simple websites to complex web applications. Here are a few of my favorites.

Event-Driven Notification System

Architected a distributed event-driven backend using Apache Kafka and consumer groups enabling horizontally scalable, asynchronous processing with at-least-once delivery semantics and safe offset management. Engineered a concurrent Go worker engine with CPU-aware pools, bounded queues, structured retries, DLQ routing, and Redis-backed idempotency ensuring duplicate-safe execution. Implemented CQRS with PostgreSQL read models and exposed via GraphQL with structured logging and Prometheus-based observability.

Go
Apache Kafka
PostgreSQL
GraphQL
Redis
Prometheus

Cloud-Native URL Shortener

Architected a cloud-native microservice backend using FastAPI with a decoupled gRPC-based analytics service to isolate traffic processing from user-facing APIs. Implemented JWT authentication with refresh token rotation, Redis-backed revocation, distributed rate limiting, and RBAC. Deployed PostgreSQL on Amazon RDS with Alembic migrations, containerized services via Docker, provisioned infrastructure using Terraform, and integrated Jenkins CI/CD pipelines.

FastAPI
gRPC
Amazon RDS
Redis
Docker
Terraform
Jenkins

Railway Crack Detection System

Developed a real-time embedded monitoring system in C++ integrating piezoelectric sensors for structural fault detection. Built a low-level data acquisition pipeline with FFT-based spectral analysis and feature extraction under strict operating constraints. Architected a multithreaded on-device classification workflow achieving 96% accuracy with deterministic execution and controlled memory footprint.

C++
Signal Processing
Embedded Systems
Real-Time Systems
Machine Learning
Hackathons

I like building things

During my time in university, I attended 0+ hackathons. People from around the country would come together and build incredible things in 2-3 days. It was eye-opening to see the endless possibilities brought to life by a group of motivated and passionate individuals.

Contact

Get in Touch

Want to chat? Just shoot me a dm with a direct question on twitter and I'll respond whenever I can. I will ignore all soliciting.

GitHub
LinkedIn