Hi, my name is Ali Rosyid

I'm

I architect event-driven microservices and stateful B2B automation pipelines. I bridge the gap between raw LLMs and production-grade business infrastructure, ensuring zero-trust security, strict deduplication, and algorithmic efficiency.

Book an Audit View Architecture

ABOUT

The Architect

AI Backend & Automation Architect

Enterprises today don't just need AI wrappers; they need intelligent pipelines that are secure, deterministic, and fully integrated with their proprietary data. I engineer robust backend architectures utilizing Python, FastAPI, Redis, and containerized environments. I build the invisible event-driven engines that ensure zero data leakage (PII compliant) and eliminate manual operational bottlenecks.

Core Architecture Stack

Python, FastAPI & Celery

PostgreSQL & Redis (Stateful Memory)

Qdrant & LangChain (Enterprise RAG)

Docker, Linux & n8n Routing

Schedule Discovery

BACKGROUND

Business Strategy Meets AI

Business Administration

Focus: Academic Foundation

Mastering core business operations, organizational scalability, and process efficiency—laying the strategic groundwork for high-ROI enterprise automation.

Enterprise Systems Architecture

Focus: Technical Specialization

Architecting and deploying high-volume B2B automation pipelines, custom APIs, and remote infrastructure using modern containerized stacks.

Programmatic Media Engineering

Focus: Advanced Integration

Developing end-to-end data-to-video architectures utilizing FFmpeg, Python, and AI-driven asset generation.

SOLUTIONS

Enterprise Case Studies

Event-Driven RAG & Automation Pipeline

API Gateway

Redis Broker

Celery Workers

Vector DB

Secure Output

Stateful AI Orchestration

Engineered closed-loop outbound engines (n8n, Llama-3). Designed custom RAM hijacking and deterministic caching to strictly prevent duplicate outreach, saving clients 100+ hours of manual SDR data entry monthly.

Enterprise RAG & LLM Engine

Deployed scalable vector search pipelines (FastAPI, Qdrant) with asynchronous processing. Implemented parallel grading microservices to systematically block LLM hallucinations and enforce strict PII redaction.

Private AI Infrastructure

Architected decoupled, event-driven backends using Redis and Celery. Bypassed API timeout bottlenecks and reduced query latency by shifting heavy LLM inference to background worker nodes within secure Docker networks.