Success Story: Indonesian Full-Stack Engineer with AI/ML Background — ¥5,700,000 / year

Hi, I’m Kotaro Muramoto, CEO of JOBs Japan. This is a success story that shows how strong AI/ML skills + full-stack proficiency + fast execution can get you an excellent role in Japan.

Candidate Snapshot

• Nationality: Indonesia

• Strengths:

  • Experience building AI & machine learning systems for global companies (USA, Singapore, Indonesia)

  • Full stack work: frontend + backend

  • Particularly strong with Node.js (backend) & Vue.js (frontend)

  • Able to prototype quickly, lead architecture decisions, and optimize systems end-to-end

Key Achievements / Projects

Some examples of what made this candidate stand out:

• Optimized GraphQL queries to improve data fetch speed by ~50%

• Reduced CPU usage by ~70% using Puppeteer optimizations

• Worked with large language models (LLMs) to extract required information automatically from contract PDFs

• Led architecture redesign and migration to a monorepo setup to boost development efficiency

• Shortened deployment time (~20%) using CI/CD tools like GitHub Actions or GitLab CI/CD

• Improved database query time from ~60 seconds down to ~10 seconds, and built automated cleanup for unused AWS S3 data

The Hiring Process & Role

• The company is an innovation management firm: they help existing enterprises and startups turn ideas & technology into scalable businesses.

• The team uses LLMs / AI to analyze global startup data and help corporations & governments collaborate more effectively with overseas startups.

• Role required a tech-lead level engineer who can work both front and backend, build prototypes fast, and participate in both architecture and hands-on coding.

• The process moved very quickly: 8 candidates interviewed via Zoom over 2 weeks, feedback tracked via shared docs and spreadsheets. This candidate was selected 2 weeks after being introduced.

Why This Candidate Was Chosen

1. Able to move fast & prototype — this reduces the time before you can start delivering value.

2. Strong AI/ML + Full-Stack + Architecture combo — many people have one or two of those, but all three is a premium.

3. Optimization & performance mindset — they didn’t just build features; they improved speed, reduced compute, optimized queries.

4. Experience across geographies / global companies — helps in understanding scale, cross-cultural teams, diverse challenges.

What This Means for You (How to Learn / Apply It)

If you want similar success, consider:

• Build concrete AI / ML projects, especially ones using LLMs or data extraction / NLP / computer vision etc.

• Be proficient in both frontend and backend so you can contribute across the stack or switch as needed.

• Gather experience in optimization, profiling, query tuning, CI/CD, performance improvements. These are often what separate “good” from “outstanding”.

• If possible, show leadership: architecture decisions, migrations, improving development efficiency.

• Be ready to respond quickly in interviews. Having your resume ready, examples & stories prepared, and being responsive speeds up the process.

Outcome & Reflection

• Annual salary offered: ¥5,700,000

• Role: Full-Stack Engineer with responsibilities spanning front & back end, prototyping, architecture, performance, AI/ML components.