Pov Lyhoung
Open to AI product roles · Remote / Phnom Penh

Hi, I'mPov LyhoungI build AI-era products that ship.

AI Product Engineer & Software Engineer

I'm an AI Product Engineer building production software for the energy sector — shipping backend, web, and mobile products end-to-end while using AI as a core part of how I design, build, and ship.

In production
7+
Years shipping
4+
Focus
AI · Product · Full-Stack
Pov Lyhoung portraitFlutterClaude MaxNext.jsTypeScript.NET
E-Power CCLCurrently building at E-Power CCL

About

An engineer wired for shipping.

Since December 2023 I've been on the engineering team at E-Power CCL, shipping seven real-world products — Solar, EAC App, Mobile Billing, E-Power Maps, E-Power Maps Desktop, E-Power Condo, and E-Power Updater. I work across the whole product surface: data model, API, client, and release. AI-augmented development has been part of that from the start — I built the first Meter Data Management System in pair-programming sessions with GPT-4 back in May 2024, and AI tooling now sits in my daily delivery loop.

How I work with teams

I'm easygoing, friendly, and respectful — a hard-working teammate who stays involved, and a leader who sees a problem through to the best solution available.

EasygoingFriendlyHard-workingActiveRespectfulOpen-mindedProblem-solverTeam Leader
How I use AI

AI Product Engineering

Shaping products around what models can actually do — spec, build, verify, ship.

Backend Engineering

REST APIs, data modeling, and system design with Node.js, .NET, and SQL / PostgreSQL.

Frontend & Web

Modern web UIs with Next.js, React, and a deep HTML / CSS / JS foundation.

Mobile (Flutter)

Cross-platform iOS & Android apps with Dart 3, REST integration, and offline flows.

DevOps & Cloud

Docker, Kubernetes, AWS, Render, Supabase, Firebase — shipping and keeping things up.

Leadership & PM

Project management and team leadership — scoping, planning, delivering.

AI Practice

AI is in the loop, not in charge.

View all
  1. 01 · Discovery

    Frame the problem before writing code

  2. 02 · Design

    Model the data and the interface together

  3. 03 · Build

    AI pair programming in the real repo

  4. 04 · Review

    Verify before it reaches production

  5. 05 · Ship

    Release, watch, and iterate