Building systems that scale — from high-performance backends to AI with Retrieval-Augmented Generation.
role: Backend & AI Engineer
core: Go · Python · C++ · RabbitMQ
flagship: Luko AI (RAG) & Chronicles-OJ
infra: Proxmox · Docker · PostgreSQL · Valkey
Informatics Engineering student at Tanjungpura University (UNTAN), focused on backend engineering and AI engineering.
Building APIs & backend systems with Go, PostgreSQL, and RabbitMQ — plus RAG (Retrieval-Augmented Generation) systems for AI chatbots. I believe great systems are scalable and measurable.
Merancang API berkinerja tinggi, database concurrency, connection pooling, dan arsitektur microservices terukur.
Membangun pipeline RAG (Retrieval-Augmented Generation) untuk chatbot cerdas dengan grounding dokumen presisi tinggi.
Mendistribusikan beban komputasi berat (evaluasi kode & inferensi AI) melalui message broker tanpa membebani web thread.
Teknologi dan tools yang saya gunakan untuk merancang sistem backend terdistribusi dan pipeline AI.
Membangun REST API berkecepatan tinggi, goroutine concurrency, connection pool tuning, dan worker backend.
Integrasi model LLM, chunking dan retrieval dokumen (RAG), vector similarity search, dan pipeline CI/CD MLflow.
Asynchronous task queue, event routing, AMQP protocol, dan pemisahan beban berat agar API tetap ultra responsif.
Pemahaman mendalam tentang memory management, struktur data kompleks, dan logika sistem kompetitif/penilaian kode.
Deep technical competencies across distributed backend architecture, AI grounding engines, asynchronous message queues, and cloud infrastructure.
Merancang dan membangun arsitektur backend berkecepatan tinggi dengan Go, optimalisasi koneksi database PostgreSQL, dan REST API terukur tanpa kompromi.
Mengintegrasikan model kecerdasan buatan dengan sistem Retrieval-Augmented Generation (RAG) berbasis vector database untuk menghasilkan jawaban presisi dari dokumen terverifikasi.
Memisahkan komputasi beban berat (seperti penilaian kode otomatis dan inferensi AI) ke worker pool terisolasi melalui message broker RabbitMQ dan Kafka.
Mengelola server virtualisasi mandiri Proxmox VE serta membangun pipeline CI/CD MLflow untuk pelatihan ulang model dan validasi metrik otomatis.
Simulasi interaktif alur sistem terdistribusi: dari API Gateway Go, RabbitMQ message queue, hingga worker AI RAG, sandbox judge engine, & Proxmox IaaS automation.
POST /v1/query: "Jelaskan struktur kurikulum Informatika UNTAN"
Token validation, rate limiter & connection pool handling
Decoupled async dispatch: routing_key='rag.inference.v1'
Top-k chunk similarity retrieval + document grounding context
Cached response & session memory with <2ms lookup
Klik "Run Simulation" atau klik node untuk menginspeksi alur sistem...
Simulasi throughput dan P99 latency comparison under 10,000 concurrent client requests.
Curated selection — distributed backend, AI & RAG, cloud IaaS, and MLOps pipelines.
AI chatbot for students asking about informatics topics. Integrates LLM models with a RAG (Retrieval-Augmented Generation) system for document-grounded answers.
LLM + RAG Document Grounding + Async Inference Queue
UNTAN's official Online Judge. Code assessment system with a Go, PostgreSQL, and RabbitMQ backend architecture.
Worker Pool + Isolated Sandbox + AMQP Task Routing
IaaS/PaaS platform built with Go, Proxmox, Valkey, OAuth2, JWT, and a local payment gateway.
Proxmox API + JWT Auth + Local Payment Gateway
MLflow CI/CD pipeline: automated retraining & deployment of a RandomForest model (breast cancer classification) with GitHub Actions. Metrics: accuracy, F1, precision, recall.
Automated Retrain + Model Registry + Metrics Validation
Milestones in distributed backend systems, AI engineering, and academic contributions at UNTAN.
Architecting a Retrieval-Augmented Generation (RAG) knowledge engine for UNTAN Informatics students. Integrating LLM models, vector database embeddings, high-precision chunk retrieval, and asynchronous worker queues.
Building high-performance REST APIs for automated code judging across thousands of student submissions. Implemented RabbitMQ task queues and PostgreSQL database concurrency.
Developing a VM provisioning platform powered by Proxmox APIs, Valkey in-memory caching, JWT & OAuth2 authentication, and local payment gateway integration.
Building automated MLflow CI/CD pipelines for automated retraining and deployment of a machine learning classification model (RandomForest) with GitHub Actions.
Studying software engineering, distributed systems architecture, advanced algorithms & data structures, POSIX operating systems, and artificial intelligence engineering.
Interested in collaborating or have a question? Send a message!
Interested in collaborating or have a question? Send a message!
Open for Backend Engineering, Distributed Systems, and AI/RAG Engineering roles & collaborations.