work

• –Built a distributed async task pipeline using Celery and Redis for LLM-powered document intelligence, decoupling processing from core workflows with reliability and observability in mind.
• –Implemented an LLM-powered document scanning feature, enabling automated extraction and categorization of structured data from unstructured receipts and invoices.
• –Contributed to API design, schema migrations, and feature delivery in a global distributed team, maintaining testing discipline and documentation practices.

Python, Django, MySQL, Celery, Redis, LLM APIs, Docker, Git

• –Defined and oversaw technical architecture for an AI Agent-powered chatbot CRM platform, working closely with engineers on system design, conversation flows, and data integration.
• –Designed prompt engineering pipelines and iterated on LLM agent behavior to meet client requirements, bridging product needs with engineering implementation.
• –Managed end-to-end API integrations including WhatsApp Business API and CRM webhooks, ensuring service reliability and alignment with client expectations across distributed touchpoints.

AI Agents, LLMs, Prompt Engineering, WhatsApp Business API, REST APIs, Python

• –Developed features and UI components for the Grab passenger app, collaborating closely with designers, backend engineers, and PMs in a cross-functional product team.
• –Implemented snapshot and unit tests across major app flows, improving release confidence and CI/CD reliability.
• –Participated in code reviews and contributed to technical documentation, maintaining high code quality standards across the team.

Swift, SwiftUI, UIKit

• –Built multiple iOS applications using SwiftUI, UIKit, and Core frameworks, focusing on performance and clean architecture with their respective backends.
• –Implemented real-time data handling and background processing for mobile applications.
• –Worked on projects involving sensor data such as computer vision, IMU (CoreMotion), and on-device ML (CoreML, Vision).

Swift, SwiftUI, UIKit, SpriteKit, CoreML, Vision, TypeScript, Hono, PostgreSQL, Firebase

• –Led a team of 6 engineers in the ongoing advancement of autonomous and manual control systems for underwater and surface vehicles using Python and ROS.
• –Designed modular perception and localization pipelines using computer vision models (YOLO, visual odometry), deployed and tested on real-world robotic systems.
• –Built software pipelines integrating IMU and camera for localization and navigation.
• –Worked closely with hardware components, microcontrollers, and embedded systems over wired and wireless communication.

Linux, Python, ROS, OpenCV, Deep Learning, Docker, Behavior Trees, Arduino, Gazebo

• –Implemented a real-time computer vision system with backend management for a scalable product management system and semi real-time inference support using Django, optimizing for speed and reliable data processing.
• –Integrated asynchronous job queues with RabbitMQ and Pika to facilitate communication between the admin interface and object detection system.
• –Contributed in designing the system architecture, ensuring scalability and efficiency.

Python, OpenCV, Pika, RabbitMQ, Django, Celery

• –Engineered and crafted the website for CEO FTUI (Universitas Indonesia's Engineering Faculty) yearly event, spotlighting job prospects for Engineering Faculty students.

Figma, Tailwind, Next.js, Vercel