Muhammed
Iqbal
Engineer at the intersection of AI, operations, and product — building internal tools that ship at scale.
14 years from field IT to applied AI. I take ML pipelines and turn them into tools people actually use.
Ops roots,
AI focus.
I started in field IT support and spent 14 years working my way through enterprise systems engineering, site launches, and fleet management.
Somewhere along the way I started automating everything — first with scripts, then with ML pipelines, then with LLMs.
Now I build AI-powered tools that solve real operational problems: the kind that cut an hour of manual research down to a minute.
I'm interested in roles where engineering means shipping things that change how people work.
What I build
Applied AI and systems work — from agentic pipelines to hardware integrations. Case studies and demos in progress.
Auto Negotiator
Multi-tool AI agent orchestrating email, calendar, and records APIs to automate procurement negotiation end-to-end.
Goal: Eliminate manual back-and-forth on routine procurement requests through autonomous agent decision-making.
Target: zero human touchpoints on standard negotiation cycles
Procurement Classifier
ML classification model integrated into a Flask web application delivering single-click procurement categorization.
Goal: Replace 4-window context switching with actionable ML intelligence surfaced directly in the workflow.
Deployed to 100+ operational stakeholders across APAC
Spatial Wayfinding System
PDF extraction → SVG processing → 3D web rendering pipeline for real-time indoor asset fault reporting and wayfinding.
Goal: Give facility and operations teams live visibility into asset status without requiring on-site presence.
Operational visibility for global facility teams across multiple sites
EUCD Device Kiosks
End-to-end hardware-software systems integration powering self-service device check-in/check-out lifecycle management.
Goal: Remove IT dependency from routine device transactions and create an auditable device lifecycle record.
500 devices managed across 3 operational sites
Zebra Printer Fleet Tool
ZPL-based headless printing engine with fleet management dashboard providing single-pane remote control of hardware.
Goal: Eliminate manual label generation errors and give ops teams remote visibility and control of all printer hardware.
95% reduction in label generation time · Global rollout across APAC and ME regions
Tourism Photobooth
Generative AI-powered photobooth experience themed around airline and tourism aesthetics.
Goal: Demonstrate end-to-end creative AI application — from prompt design to physical printed output.
End-to-end from AI generation to printed output in under 30 seconds
Tools and track record
AI / ML
Cloud & Infrastructure
Development
Operations
Career arc
Designed and deployed AI-enabled internal tooling rolled out across APAC and ME. Cut change-management research from 1 hour to under 1 minute. Won Amazon Global Hackathon, Boston 2025.
Led IT commissioning for Singapore's first Amazon Logistics delivery station in 60 days. Managed 500 devices and $70K budget. Co-created globally-launched Zebra printer fleet management tool.
Managed server estates on VMware and Hyper-V for government and commercial accounts. Developed PowerShell, VBScript, and batch automations compressing repetitive system tasks.
Field services for government accounts. Built scripting tools reducing ticket resolution time.
Certifications & training
Training
- Amazon Machine Learning University (MLU) — Applied AI/ML, 2025–2026
- Vertical Institute — WSQ Data Science, 2025
- Microsoft Azure Administrator, 2020
Let's talk
I'm exploring senior engineering roles in Singapore — AI tooling, applied AI, or product-focused engineering where shipping matters.