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I'm a final-year AI master's student at NTU with a strong passion for building AI-powered products from zero to production. My work spans LLM application engineering, multi-agent systems, and full-stack AI product development — from shipping ISolid, an idea-structuring tool built on LangGraph with tiered LLM dispatch, to architecting ShieldFlow, a multi-agent data analysis engine with RAG and sandboxed code execution. I thrive at the intersection of system design and applied AI, and I'm most energized when turning a messy real-world problem into a working, deployed product.…I'm a final-year AI master's student at NTU with a strong passion for building AI-powered products from zero to production. My work spans LLM application engineering, multi-agent systems, and full-stack AI product development — from shipping ISolid, an idea-structuring tool built on LangGraph with tiered LLM dispatch, to architecting ShieldFlow, a multi-agent data analysis engine with RAG and sandboxed code execution. I thrive at the intersection of system design and applied AI, and I'm most energized when turning a messy real-world problem into a working, deployed product.

Enge Lou

Data Scientist, AI Engineer, AI Developer, +2

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I'm a final-year AI master's student at NTU with a strong passion for building AI-powered products from zero to production. My work spans LLM application engineering, multi-agent systems, and full-stack AI product development — from shipping ISolid, an idea-structuring tool built on LangGraph with tiered LLM dispatch, to architecting ShieldFlow, a multi-agent data analysis engine with RAG and sandboxed code execution. I thrive at the intersection of system design and applied AI, and I'm most energized when turning a messy real-world problem into a working, deployed product.…I'm a final-year AI master's student at NTU with a strong passion for building AI-powered products from zero to production. My work spans LLM application engineering, multi-agent systems, and full-stack AI product development — from shipping ISolid, an idea-structuring tool built on LangGraph with tiered LLM dispatch, to architecting ShieldFlow, a multi-agent data analysis engine with RAG and sandboxed code execution. I thrive at the intersection of system design and applied AI, and I'm most energized when turning a messy real-world problem into a working, deployed product.

Available to hire

I’m a final-year AI master’s student at NTU with a strong passion for building AI-powered products from zero to production. My work spans LLM application engineering, multi-agent systems, and full-stack AI product development — from shipping ISolid, an idea-structuring tool built on LangGraph with tiered LLM dispatch, to architecting ShieldFlow, a multi-agent data analysis engine with RAG and sandboxed code execution. I thrive at the intersection of system design and applied AI, and I’m most energized when turning a messy real-world problem into a working, deployed product.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Chinese

Advanced

Work Experience

Senior Scientist I at A*STAR CFAR, Singapore

August 1, 2025 - January 1, 2026

Built deep learning pipelines in PyTorch leveraging ESM protein language models for enzyme activity prediction; designed reproducible workflows for data preprocessing, model training and inference on large, imbalanced datasets; automated 3D structure generation with RhoFold, and API-based retrieval of sequence records to support a large dataset (40w+) for RNA-ligand binding prediction.

LLM Applications Engineer Intern at Desay SV Automotive, Singapore

January 1, 2026 - May 1, 2026

Built multilingual translation plugin using locally deployed LLMs with a RAG knowledge base; co-authored an IEEE-ITSC paper on Structured Runtime Safe Monitoring for Camera-Based Driver Monitoring Systems; deployed OpenClaw for robotic arm control using ROS2 and Gazebo; developed an automated PRD-UE-UI audit system to detect inconsistencies across copy, interaction paths, components, and visual elements, reducing manual review time by 90%+ with issue detection rate exceeding 95%.