const ken = {
location: "Manila, Philippines (Remote-ready)",
role: "AI Full-Stack Engineer @ Romega Solutions",
building: ["Production RAG systems", "AI agents", "Full-stack platforms"],
shipped: "42K-LOC internal ops platform β solo, in ~3 months",
stack: ["Next.js", "TypeScript", "FastAPI", "Supabase", "pgvector", "Claude API"],
principle: "Ship AI that survives contact with real users β not just demos",
};I build production AI systems that hold up under real load β RAG pipelines, autonomous agents, and full-stack applications taken from idea to live deployment, often solo.
Most recently I shipped an all-in-one internal operations platform on my own in about three months: 46 pages, 56 API routes, a 31-table Postgres schema, ~42K lines of TypeScript β native ticketing, a recruiting ATS, an LMS, and LLM-powered reporting, plus a zero-downtime migration off a third-party PM SaaS.
My focus is the engineering that makes AI dependable, not just impressive in a demo: retrieval that surfaces the right context, agents that fail gracefully, and architectures built for reliability, cost, and scale from the first commit. AI outputs land in human review queues β never auto-published. I care less about what looks good on stage and more about what's still running at 2 AM.
Recent Highlights:
- π Champion β C(Old) (St)art Hackathon 2025 (Old St. Labs)
- π₯ 1st Runner-Up β InfoTech Olympics 2025 (PaceBeats)
- π― National Top 10 β DOST-TAPI ClustRICE 2025 (HerbaLens, 53 entries)
- π€ Speaker β Qwen Meetup Manila #2 (Alibaba Cloud PH)
AI Full-Stack Engineer @ Romega Solutions Β· Remote Jul 2025 β Present
- Shipped an all-in-one internal operations platform solo β 46 pages, 56 API routes, a 31-table Postgres schema, ~42K lines of TypeScript in ~3 months (PM/ticketing, attendance, recruiting ATS, LMS, AI reporting).
- Led a zero-downtime migration off a third-party PM SaaS: rebuilt ticketing natively (kanban, sprints, comments, activity feeds), migrated SQLite β Supabase Postgres with Drizzle ORM, replaced custom JWT auth with Supabase Auth + Google OAuth.
- Integrated LLM features (executive briefings, AI status-report drafting) and n8n automations (resume parsing, applicant comms, multi-step onboarding) into business workflows β outputs route to human review queues, never auto-publish.
- Shipped production RAG chatbots with vector embeddings (ChromaDB Β· sentence-transformers Β· Gemini) for customer interactions and workflow automation.
Lead Software Engineer @ PaceBeats Β· Remote Aug 2025 β Mar 2026
- Architected a biometric music platform (1st Runner-Up, InfoTech Olympics 2025): WearOS app (Kotlin, Health Services API), Android app, React/TypeScript dashboard, Supabase backend.
- Built a hybrid recommendation engine combining rule-based pace-to-BPM mapping with content-based ML scoring β real-time playlist adaptation.
- Engineered the WearOS companion: GPS tracking, heart-rate monitoring, Data Layer API sync, Spotify SDK, 8+ hour battery optimization.
Software Engineer (Contract) @ CodeVF Β· Remote Feb 2026 β Apr 2026
- Built a real-time collaboration platform with WebSocket architecture for live debugging sessions between customers and engineers β bidirectional code review and remote assistance.
AI Workflow Automation Engineer @ University of Makati Β· Remote Jan 2026 β Apr 2026
- Built n8n automation workflows to streamline administrative processes and data pipelines.
Earlier: VCM hardware deployment for COMELEC national elections (2025); enterprise SaaS technical support at Concentrix (2024).
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AI Legal Compliance Assistant RAG-powered chat for navigating Philippine legal compliance, evaluated against a golden question set. Stack: Next.js, RAG, Claude API, Vector DB Highlights:
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Biometric Music Platform Real-time music recommendation that adapts to a runner's pace and heart rate. Stack: React Native, Kotlin, WearOS, Spotify API, Supabase, ML Highlights:
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Automated Certificate Generator Open-source, self-hosted certificate platform with workflow automation and bulk processing. Stack: Next.js, Tailwind CSS, n8n, PostgreSQL Highlights:
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Medicinal Plant Recognition Android app identifying medicinal plants with on-device computer vision. Stack: Android, TensorFlow, Computer Vision Highlights:
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On-Demand Mechanic Platform Mobile app connecting vehicle owners with professional mechanics. Stack: Flutter, Firebase Highlights:
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Counseling Platform Mobile guidance-counseling system with mood tracking and sentiment analysis. Stack: Flutter, Firebase, AI/ML, Cloud Functions Highlights:
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π Competition Awards
| Achievement | Event | Year |
|---|---|---|
| π₯ Champion | C(Old) (St)art Hackathon, Old St. Labs | 2025 |
| π₯ 1st Runner-Up | InfoTech Olympics 2025 (PaceBeats) | 2025 |
| π Best Paper (97%) | 8th Research Congress, UMak (ARS) | 2025 |
| π― National Top 10 | DOST-TAPI ClustRICE β 53 entries (HerbaLens) | 2025 |
π€ Speaking & Community
- Speaker β Qwen Meetup Manila #2, Alibaba Cloud PH (2026)
- Community Officer β AWS User Group PH, Community Day 2026
- DataCamp Scholar β Data Engineering Pilipinas (selective program, 2025βpresent)
- Technical Committee β UMak Computer Society, 15+ campus events



