AI Engineer / Houston, TX
Ahmad Ferdaws Shafiq standing in Washington, DC
profile / ferdaws
ai/ml engineer

Ahmad Ferdaws Shafiq

CS Undergrad / AI Engineer / Houston, TX

AI Engineer focused on systems that ship. I design and build production agentic pipelines, ML models, and automation infrastructure that solves real problems at scale.

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About

Builder Profile

I'm Ahmad Ferdaws Shafiq, a Computer Science student at North American University and AI Engineer based in Houston, Texas. My interest in technology started early and never stopped growing. Over time that curiosity became a discipline: building systems that are technically rigorous, production-ready, and actually useful.

Today I work across agentic AI, machine learning, and automation infrastructure, and I'm pursuing graduate research to push further into what's possible with AI systems.

90%
Manual workload reduced
1K+
Documents per week
40+
Staff hours saved / cycle
systems consoleagent mesh
ai systems / automation
SchoolNorth American University
LocationHouston, TX
FocusAgentic AI
Featured Projects

Production Systems

Use the cards to scan what shipped, what it does, and the stack behind it.
live system
AI workflow
01 / Featured

Anna - Agentic Placement Automation System

A production AI agent built to automate contractor placement operations at scale. Processing over 1,000 documents per week, Anna autonomously stages candidates through the placement pipeline - work that previously required continuous manual effort from the recruiting team. The system reduced manual workload by approximately 90%, freeing staff to focus on higher-value decisions.

n8nClaude APIBullhorn CRMTwilioGmailSupabasePostgreSQLMicrosoft SQL Server
Internal company project
live system
brain signal
02 / Featured

MOVE - Motor Output vs. Visualized Execution

An end-to-end 64-channel motor-imagery EEG pipeline built for 4-class intention decoding across 86 subjects and 7,000+ trials. Applied subject-independent GroupKFold validation with EEGNet and Riemannian ML, achieving 42-45% balanced accuracy against a 25% chance baseline. Deployed as a real-time inference API with confidence scoring, artifact detection, and ABSTAIN safety gating for interpretable BCI output.

PythonMNE-PythonTensorFlow / KerasScikit-learnFastAPI
GitHub
live system
agent loop
03 / Featured

Multi-Agent Task Orchestrator

A multi-agent system where four specialized AI agents collaborate under a central orchestrator to handle complex, multi-step tasks. Built with a production-grade backend, persistent task state, and a live React dashboard for monitoring agent activity in real time.

FastAPIPostgreSQLReactTypeScriptClaude API
More Projects

Also Built

live system
admission flow
Platform

Admission Copilot

AI-powered university program discovery and application management platform. Personalized program matching, task-list generation, and guided planning workflows backed by a scalable Prisma + PostgreSQL data layer.

Next.jsTypeScriptTailwind CSSPrismaPostgreSQLGemini API
GitHub
live system
security sandbox
Hackathon / 7th Place

AI Agent Security Sandbox

Adversarial evaluation framework for browser-based AI agents. Tests against prompt injection and unsafe action patterns with reproducible evidence logging, context-aware risk scoring, and remediation reporting.

PythonPlaywrightStatic AnalysisNVIDIA Nemotron
Experience

Work History

VC5 Partners

AI/ML Engineer Intern
February 2026 - Present

Built AI systems for legal document review, recruiter onboarding, and accounting automation. Delivered a 3-agent legal document pipeline with Claude AI, FastAPI, Azure Document Intelligence, and pgvector; built recruiter onboarding automation replacing roughly 90% of manual back-office work across Bullhorn, Magnit, Twilio, PostgreSQL, and n8n; and connected QuickBooks to Claude-powered agents through Flask middleware and a Cloudflare tunnel to reduce manual data entry.

North American University

Automation Engineer (Student)
May 2023 - Present

Built admissions automation systems that sorted and routed student applications, reducing processing time by 32% and manual errors by 41% across 3 admissions cycles using Salesforce Flows, validation rules, and REST integrations. Created 8 n8n workflows to screen applications and connect email and document systems, saving roughly 40 staff-hours per cycle across 700+ applications.

Certifications

Verified Signals

Generative AI LLMs

NVIDIA Certified Professional / NCP-GENL

Accelerated Data Science

NVIDIA Certified Professional / NCP-ADS

Writing

Notes Coming Soon

Coming Soon

Words in progress.

Writing on agentic AI systems, machine learning infrastructure, and the occasional deep dive into whatever I'm building.

Open to opportunities

Let's Connect

I'm currently open to internship opportunities, research collaborations, and PhD program connections in AI and machine learning. If you're working on something interesting, reach out.

Email MeLinkedInGitHubResume