From Core Backend Engineering to Agentic AI Architecture
Key philosophical shifts required when moving from deterministic Java environments to probabilistic multi-agent AI ecosystems.
Senior Java Backend Engineer bridging the gap between scalable cloud infrastructure, side builds, and agentic AI workflows.
Distributed data services processing 8B+ monthly requests with >99.999% uptime across production environments.
Boosted processing capacity by migrating payload serialization to Protobuf — delivering dramatic throughput gains at scale.
Built LangGraph ReAct architectures and Claude-powered automation agents, boosting end-user productivity by 80%.
Top 10 Finalist — Generative AI Hackathon. Runner-Up — EMEA IoT Hackathon. Built under 48-hour crunch conditions.
Things I build in the margins — solving real problems, exploring new stacks, and occasionally shipping.
Autonomous job application agent — reads Gmail job alerts, navigates to each listing with a Claude-powered browser agent, fills the application form, and queues it for human review before submission.
This portfolio — statically prerendered Next.js 14 App Router site with an MDX content layer, Framer Motion animations, and a server/client component split that keeps fs reads strictly server-side. Deployed to Vercel via GitHub push.
Startup concepts & architecture drafts — blueprints, open-source ideas, and startup theories I'm actively whiteboarding.
Whiteboarding new B2B SaaS frameworks, agentic automation blueprints, and interactive technical RFCs. Check back soon.
Key philosophical shifts required when moving from deterministic Java environments to probabilistic multi-agent AI ecosystems.
An architectural deep-dive into scaling distributed enterprise SaaS platforms using Java, Spring Boot, and AWS-native workflows.
How swapping traditional JSON REST payloads for Protocol Buffers boosted data throughput capacity from 350 to 1000 requests per second.