Building production-style AI + SaaS systems with FastAPI, Next.js, PostgreSQL, and LLM workflows — shipped as deployed MVPs.
I'm Rami Afif. I design and build AI and SaaS products end-to-end — from FastAPI / PostgreSQL backends to Next.js / TypeScript frontends — and ship them as deployed, clickable MVPs. Recent work includes a multi-tenant Storefront + POS SaaS and a full-stack AI productivity platform, alongside a set of focused AI demo apps.
A developer who never stopped coding—from enterprise systems to AI platforms
I'm a Computer Engineering graduate (2009) pivoting back to tech after 12 years in construction project management. That background—coordinating complex schedules, resources, and workflows—shapes how I approach building systems today.
My software career started with 2 years as a Visual Basic Developer (2010-2012) at Saranay Recruitment, building enterprise hiring systems with VB + SQL Server. That's where I learned what production code means. During my construction years, I occasionally coded websites and trading bots as hobby projects—staying connected to programming but not at a professional level.
I started exploring AI in December 2022 when ChatGPT launched. In November 2024, I committed fully to becoming an AI Engineer. After 10 months of intensive study, I earned my Associate AI Engineer certification from DataCamp (November 2025).
Then I went into build mode. Over a focused build period, I built and shipped two full-stack platforms — a multi-tenant Storefront + POS SaaS and APE (an AI productivity engine) — plus a set of focused AI demo apps on Streamlit Cloud. These aren't tutorial copies; they're working systems solving real problems.
My platforms are production-style. My Storefront + POS SaaS uses FastAPI, a multi-tenant PostgreSQL design, and Redis with a Next.js / TypeScript frontend and AWS deployment services; APE pairs FastAPI + PostgreSQL + Redis + ChromaDB with multi-agent orchestration, async batch processing, and Docker-based deployment designed for low-latency responses under concurrent use. This is the kind of full-stack AI + SaaS work I want to do professionally.
Takes features from idea to a deployed demo solo — I plan, build, and release.
Builds complete flows — storefront, dashboard, POS, API, and database — not isolated scripts.
Uses AI tools seriously — but with human review, testing, and a proper Git workflow.
Turns an idea into a working, deployed MVP a hiring manager can click through.
Built and deployed two full-stack platforms — a multi-tenant Storefront + POS SaaS and APE (AI productivity engine) — plus a set of focused AI demo apps spanning RAG, multi-agent workflows, and GPU-accelerated ML.
Dual track: Professional project management + Personal software development
Day job: Holyland Construction • Managed project scheduling, resource allocation, and budget tracking. Created daily/weekly/monthly work programs, material requirement planning (BOM), progress reports for contractors and clients.
After hours: Built websites for internet marketing, developed trading bots, experimented with new frameworks and tools—never stopped coding
Saranay Recruitment • Built enterprise hiring system with VB + SQL Server used by recruitment business
Universidad De Zamboanga
Full-Stack AI Engineer / AI Engineer / AI Developer roles where I can build production-style AI + SaaS systems, work with LLMs, and ship features that matter. Remote-friendly, ready to start immediately.
Two full-stack platforms I designed, built, and deployed end-to-end.
Full-Stack, Multi-Tenant SaaS Platform
A production-style, full-stack SaaS platform for merchants — with storefront checkout, a POS cashier workflow, inventory tracking, product variants, customer records, sales analytics, shipping / delivery, bilingual English / Arabic UI, and AI-assisted dashboard workflows.
Built merchant workflows across storefront, dashboard, and POS, with per-tenant data isolation.
Inventory, stock movements, product variants, customer history, and sales reporting.
FastAPI, PostgreSQL, Redis, Next.js, TypeScript, Docker, and AWS deployment services.
English / Arabic UI support and an AI-assisted dashboard experience for everyday tasks.
Live demo may require backend / demo availability.
Full-Stack AI Platform (production-style)
A full-stack, production-style AI platform delivering multiple capabilities through a unified interface. Built with a production-first architecture (FastAPI + PostgreSQL + Redis + ChromaDB) and designed for low-latency responses under concurrent use. Features multi-agent orchestration, RAG pipelines, and async batch processing with real-time tracking.
Context-aware chat with memory persistence and multi-turn reasoning
Firecrawl integration with AI synthesis for intelligent data extraction
AI-powered code writing and review with syntax validation
AWS Textract integration for document data extraction
10 concurrent files with async operations and real-time progress
FastAPI + PostgreSQL + Redis + ChromaDB with JWT auth
Focused AI demo apps showcasing diverse capabilities — RAG, LLMs, ML, and computer vision.
June 2026
A human-governed Architect–Implementer Challenge system for building production-style AI and SaaS systems with structured challenge, independent diff review, and traceable verification.
Type: Engineering Workflow Article