Shafiq Ur Rehman
Cloud & DevOps Engineer
I build backend services and ship them to production — AWS, Docker, CI/CD, microservices.
I design APIs, containerize them, wire up automated tests and deployment pipelines, and run them on AWS. Most recently I built and deployed FraudGuard, a real-time fraud detection service — XGBoost model behind a FastAPI endpoint, tracked with MLflow, tested with pytest, shipped through GitHub Actions to EC2. I also spent six months training and evaluating LLMs at Turing, and I've been mentoring DSA at Dev Weekends for over a year.
About
What I build, and where I'm heading next.
My Journey
I'm a software engineer in Lahore. I started in full-stack web development — Next.js, Node.js, MongoDB — and built things people could actually use: an LMS with DRM-protected lecture streaming, a multi-vendor marketplace with card and cash-on-delivery checkout.
Somewhere in there the interesting problem stopped being "does the feature work" and became "how does this thing stay up." That pulled me toward infrastructure. Now I containerize what I build, put it behind a CI/CD pipeline, and deploy it to AWS — and I'm working through Kubernetes and event-driven microservice patterns to go deeper.
The AI work runs alongside it. Six months at Turing authoring and evaluating competitive programming problems for RLHF training, plus certifications in RAG, fine-tuning, and agentic systems. I write about it at Dev.to and teach algorithms to 300+ students through the Dev Weekends fellowship.
Currently focused on
Kubernetes and container orchestration beyond single-instance Docker
Event-driven microservices — message queues, service boundaries, failure modes
Observability: metrics, logging, tracing
Open source contributions, working toward GSoC / LFX Mentorship in the CNCF ecosystem
Technical Skills
Grouped by how deeply I've actually worked with them.
Built and shipped with
Working knowledge
Learning now
Professional Journey
Building scalable systems and digital solutions across diverse technology stacks through hands-on development and collaborative problem-solving.
AI Engineer & LLM Trainer
Turing (Contract)
Authored, solved, and evaluated 150+ competitive programming problems in Python and C++ over four months, averaging two accepted problems per day, as training and evaluation data for RLHF. Validated model-generated code against official documentation and isolated edge cases and logical gaps where the model's reasoning broke down.
Key Achievements
- Recognized as Top C++ Coder on the Turing platform.
Technologies Used
DSA Trainer & Mentor
Dev Weekends Fellowship Program
Fifteen months running DSA (C++) training for 300+ students — weekly sessions, one-on-one mentoring, progress tracking. Ten-plus recorded sessions published, covering scalability fundamentals, authentication and authorization, React internals, and algorithm patterns.
Technologies Used
Software Engineer Intern
Stem Solutions
Shipped 12 production screens for a cross-platform Android and iOS app in React Native and TypeScript. Built a reusable component library and cut initial screen load time by 25% through render optimization.
Technologies Used
Featured Projects
Innovative solutions that bridge MERN stack technology with real-world impact
E-Commerce Platform
A marketplace where vendors self-register and manage their own catalogs. Multi-category product support, order management, and checkout with both card payments and cash on delivery. Containerized and deployed on AWS EC2.
Aurora ChatBot
A MERN commerce app with a built-in conversational assistant for product discovery, plus an admin panel for catalog and inventory management.
Elearning
A full learning platform with JWT auth, DRM-protected lecture streaming through VdoCipher, and separate student and admin dashboards. Redis caching cut repeat API response time by 40%. Deployed on AWS EC2.
Expense Tracker
A React Native expense tracker with local SQLite storage, category breakdowns, and spending charts.
Writing & Speaking
Long-form technical writing and recorded sessions.
Retrieval-Augmented Generation (RAG): How It Works, 10 Advanced Techniques, and Common Limitations
Simplified breakdown of execution context and call stack.
From Simple LLMs to Reliable AI Systems: Reflexion Agents with LangGraph
The article covers why single-pass LLMs are unreliable and how Reflexion fixes this by making AI agents critique and retry their own outputs. LangGraph provides the infrastructure to wire that self-correction loop together.
How to Choose the Right AI Model for the Right Job
Explores different AI models, their strengths and trade-offs, and provides practical guidance on selecting the right model based on the problem, performance, cost, and real-world use case.
How React Achieves High Performance, Even With Extra Layers
Explains how React optimizes performance despite abstraction layers.
JavaScript Execution Context Made Simple
Simplified breakdown of execution context and call stack.
Performance & Scalability Fundamentals
Delivered an in-depth session on performance and scalability, covering latency, throughput, caching, load balancing, horizontal and vertical scaling, fault tolerance, and system design concepts through real-world architecture diagrams.
State Managment In React
A deep-dive session on React state management — covering component vs application-level state, prop drilling, Context API, and performance optimizations like Virtual DOM diffing and Fiber's priority-based reconciliation.
Authentication Authorization & Security
Delivered an in-depth session on authentication and authorization, covering session-based authentication, JWT, OAuth 2.0, Google Authentication, security best practices, and interview-focused questions with real-world implementation concepts.
JavaScript Under the Hood
Delivered a live technical session on JavaScript Under the Hood, explaining the JavaScript engine, execution context, call stack, event loop, memory management, and asynchronous programming concepts.
DSA Session: String Theory & Core Concepts
Delivered an session on string concepts, covering common string operations, optimization techniques, and the foundations required for coding interviews.
DSA Problem Solving: Strings with Leetcode Problems
Solved string problems with coding examples, explaining optimized approaches, interview-focused solutions, problem-solving mindset, edge cases, and time and space complexity analysis.
DSA Session: Slow & Fast Pointers Fundamentals
Delivered an session on the Slow & Fast Pointer technique, covering its core concepts, pointer movement strategies, common use cases, and the intuition behind solving coding interview problems efficiently.
DSA Session: Slow & Fast Pointers Problem Solving
Solved Slow & Fast Pointer coding problems step by step, focusing on interview-ready solutions, problem-solving mindset, optimized approaches, and edge cases.
DSA Live Session: Arrays with Leetcode Problems
Delivered a live problem-solving session on LeetCode arrays, solving multiple array problems step by step while explaining the thought process, optimal approaches, and time and space complexity analysis.
Arrays (Part 2) with Leetcode Problems
Conducted a continuation session on array problem solving, covering more LeetCode challenges with a focus on pattern recognition, algorithmic thinking, optimized solutions, and coding best practices.
Committed to staying current with the latest technologies and best practices
Certifications Achievements
Validating technical expertise through recognized certifications and competitive programming success.
ICPC Asia Topi Online Preliminary Contest
ICPC Foundation
Honorable Mention in the 2024 ICPC Asia Topi Online Preliminary Programming Contest.
Dev Weekends Bronze Fellowship
Dev Weekends
Awarded the Bronze Fellowship by Dev Weekends in recognition of steady effort, perseverance, continuous learning, and positive contribution throughout the fellowship journey.
AI Engineer Core Track: LLM Engineering, RAG, QLoRA & Agents
Udemy
Completed an advanced AI Engineering program covering Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), QLoRA fine-tuning, AI agents, vector databases, prompt engineering, and production-ready AI application development.
Microservices with Node.js and React
Udemy
Completed a comprehensive course on building scalable microservices using Node.js and React, covering event-driven architecture, Docker, Kubernetes, authentication, testing, CI/CD, and production-ready distributed systems.
AI Engineer Agentic Track: The Complete Agent & MCP Course
Udemy
Completed an advanced course on building autonomous AI agents using the Model Context Protocol (MCP), agent workflows, tool integration, memory, planning, and multi-agent systems for real-world AI applications.
Get in touch
I'm looking for cloud, DevOps, and backend engineering roles. Open to remote and to relocation.