Hamid Khan

Software Engineer • Backend & Distributed Systems • Applied AI

Designing scalable backend systems
that survive the real world.

Backend-focused software engineer with strong foundations in data structures, system design, and cloud infrastructure. I build and operate production systems used by 1,000+ real users, focusing on performance, reliability, and clean architecture.

View Engineering Work Resume (PDF)
LeetCode: 200+ solved
Latency: ~50ms avg
Cloud: AWS • Linux • Docker

About

I am a backend & systems engineer who enjoys solving problems around scalability, performance, and reliability. I’ve worked on real production systems — not just demos — and learned how design decisions behave under actual user traffic.

I value clean system design, clear communication, and learning through failure analysis.

Engineering Impact

Experience

Software Engineer (Backend & Systems) — Admissions Express

2024 – Present

  • Designed and built backend services supporting 1,000+ users.
  • Implemented NLP-based recommendation workflows and chatbots.
  • Deployed containerized services on AWS using Linux and Docker.
  • Handled production incidents, performance bottlenecks, and reliability issues.

AI Engineer (Applied AI) — Xvantech AI Solutions (US)

June 2024 - August 2024

  • Built applied AI pipelines for automation and analytics.
  • Worked with datasets of 27,000+ records.
  • Integrated models into backend APIs and workflows.

Web Developer — Z’vis Pixelon

2023 – 2024

  • Built and maintained production web applications.
  • Focused on performance, reliability, and clean UI.

How I Think About Engineering

Selected Projects

LinguaCoach — Microsoft Imagine Cup

  • AI-powered learning platform with persistent learner memory.
  • Diagnoses recurring weaknesses in aptitude and proficiency tests.
  • NLP-driven adaptive coaching and feedback loops.

Scalable URL Shortener

  • High read-throughput system using Redis caching.
  • PostgreSQL for durability and consistency.
  • Rate limiting, TTL cleanup, and collision handling.
  • CDN + load balancer for global performance.

Computer Vision Projects (NVIDIA)

  • Crack detection using CNN-based models.
  • Image classification with GPU-accelerated training.
  • Hands-on deep learning keystone projects.

System Design

Scalable URL Shortener — Architecture

High-level design for a read-heavy URL shortener focusing on low latency, scalability, and fault tolerance.

URL Shortener System Design Diagram
  • Stateless API servers behind a load balancer
  • Cache-first reads using Redis (hot URLs)
  • PostgreSQL as the source of truth
  • Rate limiting and abuse protection
  • CDN for global redirect performance

Full design notes and tradeoff analysis available in the GitHub repository.

View Code & Design

Engineering Failures & Learnings

Department Software Platform — Scope Failure

  • Attempted to build an all-in-one platform for an engineering department.
  • Scope included attendance, academics, workflows.
  • Complexity exceeded realistic ownership and timelines.
  • Learning: Scope control and incremental delivery matter more than ambition.

Swift Go Delivery — QR & SSL Constraint

  • Built QR-based booking with location tracking and WhatsApp notifications.
  • Browser SSL and permission constraints broke real-world usage.
  • System worked locally but failed in production mobile contexts.
  • Learning: Real-world constraints dominate theoretical designs.

Skills

Achievements & Certifications

Contact

Open to Software Engineering Intern / New Grad roles.

Email LinkedIn GitHub