> I design distributed systems, event-driven microservices, and cloud-native platforms — most often as the first backend hire on a greenfield product.
> At BARQ, that meant owning merchant payments from a blank repo. At John Deere, it meant building an industrial machine-simulation platform (KleeFlow) and the AI agent that runs on top of it.
> Core stack: Java + Spring Boot, wired together with Kafka, Kubernetes, PostgreSQL, and Redis — with a growing focus on running LLMs and inference systems reliably inside production backends.
Systems built from nothing.
Three builds — pulled apart into what actually happened under the hood.
Simulation software that models a full crushing-and-screening plant — excavator, mobile screener, mobile crusher — before any machine touches a quarry. Built the core Spring Boot services and simulation backend from scratch, then shipped an AI agent that runs the machines with real-time decisioning and self-recovery. The engine originally staged each unit sequentially and timed out under load; rearchitected so the whole plant simulates in parallel, which is what shipped.
Greenfield merchant payments product — owned backend architecture from zero to production across onboarding, KYC/compliance, settlements, disbursements, and cash-in workflows. Async transaction pipelines on Kafka and Airflow, tuned for throughput and reliability under production load.
A from-scratch C++17 motion planner for a double-integrator quadrotor: a closed-form optimal boundary-value solution (depressed-quartic arrival time) serves as both the steering function and the RRT* cost metric, with choose-parent/rewiring for asymptotic optimality. Success rate climbs from 15% to 100% and mean path cost drops from 26.9 to 24.5 as the iteration budget grows, producing dynamically feasible curved 3D trajectories through obstacle fields. Ships with an interactive Dear ImGui/raylib editor with background-thread replanning, a headless OpenCV renderer for CI, 27 GoogleTest unit tests, and a GitHub Actions matrix across GCC/Clang.
Side projects, current.
Where I've built.
- Founding engineer for Pay by BARQ — merchant payments backend, zero to production.
- Event-driven Spring Boot microservices across auth, onboarding, KYC/compliance, core-banking workflows.
- Async transaction pipelines with Kafka and Airflow for reconciliation and scheduled payments.
- Founding engineer of KleeFlow, a road-building machine simulation platform — core Spring Boot services and simulation backend.
- Shipped an AI agent for autonomous machine operations with real-time decisioning and self-recovery.
- Integrated BERT/BART inference into the Java backend via Python orchestration, Kafka, and Airflow.
- Improved API latency 20% through PostgreSQL tuning, Redis caching, and indexing.
- Built an AI-powered hiring platform on Quarkus, GraphQL, and Hibernate with automated ETL — 70% less manual effort.