Backend / systems engineer · Lahore, open to remote roles

About Mubashir Rehman

I build the systems behind messy, multi-system workflows, and then I keep them running. My habit is to find the problem, understand the system underneath it, build the fix, and stay for what breaks next.

Mubashir Rehman Mubashir Rehman

Mubashir RehmanLahore · UTC+5

At TransData, where I have led a team of five engineers since March 2026, I took an AI voice front desk for dental clinics from AI-scaffolded code to a production launch, then designed and deployed its AWS backend on services verified as HIPAA-eligible. I have also built agents that work inside a live ERP, and a social-signal intelligence backend I wrote alone for a client.

Before that, at VeritusLabs, I was promoted to team lead about three months in and led four engineers on drone-control software. For five semesters I was a teaching assistant for operating systems at Information Technology University.

How I work

All ten rules. Each one came out of real work, and the link is the evidence.

  1. Rule 1: Read the number that does not add up.

    From An AI voice front desk for dental clinics →

  2. Rule 2: Split diagnosis from fixing where the blast radius changes.

    From A harness for AI coding agents near production →

  3. Rule 3: Prove the path end to end before you tune the thresholds.

    From A social and market signal intelligence backend →

  4. Rule 4: Keep the adapter generic. Put business rules where the business trigger lives.

    From AI agents working inside a live ERP →

  5. Rule 5: A partial result should look partial.

    From An operations console for a healthcare integration engine →

  6. Rule 6: Check the vendor's own list, not your memory.

    From A production AWS backend on HIPAA-eligible services →

  7. Rule 7: Write the specification first, and trace every requirement to a screen.

    From Architecture for a multi-tenant lead-intelligence SaaS →

  8. Rule 8: Deterministic first, model second.

    From HireTrack: an AI résumé tailor and job-application tracker →

  9. Rule 9: Report a result with its sample, or do not report it.

    From Low-cost single-lead ECG for vascular-age prediction →

  10. Rule 10: Give the agent today's docs, not its memory.

    From Skills and model routing for AI coding agents →

The path

Full-time roles count toward the 3+ years; teaching and the internship do not.

  1. to now

    Lead Software Engineer, TransData

    Leads five engineers: one AI engineer and four full-stack engineers. Backend, AI and infrastructure across healthcare, ERP and AI products. Now: an AI voice front desk for dental clinics and its AWS backend.

    Full-time

  2. to

    Software Engineer, TransData

    Backend, AI and infrastructure across healthcare, ERP and AI products.

    Full-time

  3. to

    Software Engineering Team Lead, VeritusLabs

    Promoted about three months in. Led four engineers on drone-control software in C++ and Qt/QML. Built an AI prompt-management app and scripted AWS provisioning.

    Full-time

  4. to

    Software Engineer, VeritusLabs

    Drone ground-control features in C++ and Qt/QML.

    Full-time

  5. to

    Teaching Assistant, Information Technology University

    Operating systems: undergraduate labs for three semesters (50+ students), graduate Advanced Operating Systems for two (30+ students).

    Part-time, alongside full-time work

  6. to

    Game Development Intern, GameBole Studios

    Android and web endless-runner games in Unity and PlayCanvas.

    Internship

Teaching and research

Explaining systems, and measuring them.

Teaching assistant, operating systems

For five semesters I was a teaching assistant for operating systems at Information Technology University: I ran undergraduate labs on file systems, threads, scheduling, system calls and synchronisation, discussed classic systems papers with graduate students, wrote assignments under the instructor and graded projects.

Research · Circuits, Systems, and Signal Processing (Springer), 44(8), 5852 to 5875, 2025

Evaluation of a low-cost single-lead ECG module for vascular ageing prediction and studying smoking-induced changes in ECG

Co-author with equal contribution, third of seven authors. My part: data collection, the signal-processing and feature pipeline, and model training and evaluation. 42 subjects and 6,131 segmented samples; a random forest reached R² 0.99 on segmented data and R² 0.87 with transfer learning on unsegmented data.

Education and stack

Where it started, and what I use now.

BS Computer Science

Information Technology University, Lahore.