Aman Zainal is an engineer based in Kuala Lumpur / Singapore and former founding AI engineer at AIRAP. He earned a B.Eng. in Mechanical Engineering with a Second Major in Computer Science from the National University of Singapore. Earlier, he received the Singapore Ministry of Education's ASEAN Scholarship for pre-university study. He builds production AI products that survive past the demo — aviation compliance audit tools, B2B operations platforms, research interpretability layers, and generative AI pipelines on a local 4-GPU rig. He is available now for full-time roles and collaborations.
Download résumé (PDF)
Selected work
- AIRAP / Aero Plus Platforms — aviation compliance audit, EASI B2B ordering platform, and AeroPlus Exchange (APE), an AI-brokered aircraft-parts marketplace. ~95% analyst-graded audit accuracy; two engineers built a fully functional EASI version in two weeks.
- Forecast Interpreter (A*STAR ARTC) — conversational interpretability layer over A*STAR's internal demand-forecasting models. Cuts planner workflow from ~40 minutes to ~2 minutes per forecast.
- Hyundai Singapore (HMGICS) — DevOps engineer; planned and drove a monolith-to-19-server service-isolation migration and built ThingWorx applications for HMGICS's connected-manufacturing platform.
- Banyan — collaborative family-tree app with realtime graph rendering and share-link onboarding. Next.js 16, Supabase Realtime + RLS, React Flow.
- Virtual Wardrobe — generative AI clothing try-on platform; FastAPI gateway, Vite/React web, Expo React Native, ComfyUI on RunPod GPU.
- Real or AI eye test — twelve-plate guessing game; half public-domain photos, half generated locally on the 4-GPU rig.
Site map
- Work — selected systems and projects
- Real or AI — eye-test game powered by local diffusion models
- Stack — the image-pipeline rig
- Contact — background, education, Telegram, email, GitHub, LinkedIn
- Resume (PDF)
Elsewhere
Find Aman Zainal on GitHub, LinkedIn, and Telegram. Email: amanzainalsventures@gmail.com.