Professional Summary
Software Engineer graduating from FAST NUCES (2026) with hands-on experience building full-stack applications,
AI-powered tooling, and DevOps automation systems. Proficient across the MERN stack, Python/FastAPI, Flutter,
and containerization with Docker & Kubernetes. Built production-grade projects including an AI-powered DevOps
deployment platform, MLOps pipelines, and multi-agent AI systems. Strong focus on writing clean, maintainable
code and delivering software that solves real problems.
Technical Skills
Languages
JavaScript, TypeScript, Python, C++, Java, Dart, SQL
Web / Backend
React, Next.js, Node.js, Express.js, FastAPI, Flask, MongoDB, SQL Server
Mobile
Flutter, React Native
AI / ML
Google Gemini API, OpenAI Whisper, Ollama (Qwen/Llama), Scikit-learn, MLflow, Apache Airflow
DevOps / Cloud
Docker, Kubernetes, Terraform, GitHub Actions, CI/CD Pipelines, Prometheus, Grafana
Tools
Git, Figma, Vercel, DVC, Dagshub, Swagger, Notion API, Slack API
Education
Bachelor of Science in Software Engineering
2022 – 2026
FAST National University of Computer and Emerging Sciences (NUCES)
Key Projects
- Built full-stack AI-powered DevOps platform that automates Docker & Terraform configuration generation
- Integrated local LLM (Qwen2.5-Coder via Ollama) for intelligent Dockerfile and docker-compose generation with SSE streaming
- Developed hybrid heuristic + ML analysis pipeline detecting language, framework, ports, databases, and services automatically
- Implemented multi-service detection for monorepo projects with per-service Dockerfile generation
- Built React/TypeScript frontend with real-time build/deploy progress streaming and Docker management UI
- Built end-to-end MLOps pipeline for real-time predictive modeling with automated data ingestion and model retraining
- Orchestrated ETL workflows using Apache Airflow DAGs with scheduled data extraction from live APIs
- Versioned datasets with DVC and tracked experiments via MLflow integrated with Dagshub
- Established CI/CD pipeline with GitHub Actions and CML for automated testing and model comparison
- Containerized ML model serving API using Docker with FastAPI, deployed monitoring stack with Prometheus and Grafana
- Developed multi-stage AI pipeline transforming voice recordings into structured team digests with cross-team blocker detection
- Integrated OpenAI Whisper for local speech-to-text and Google Gemini for structured JSON extraction
- Built semantic clustering using Gemini embeddings + Agglomerative Clustering for thematic grouping
- Automated daily delivery to Slack channels and Notion pages with APScheduler cron jobs
- Built interactive route planning tool using genetic algorithms for optimal delivery sequence calculation
- Developed Flask REST API with /optimize endpoint running GA solver in real-time
- Created dark-mode Leaflet.js map UI with animated path visualization and glassmorphism panel
- Created cross-platform mobile car booking application using Flutter framework
- Designed and implemented intuitive UI with reusable component library for consistent experience
- Built complete navigation flow for seamless booking and reservation management
- Designed comprehensive UI/UX in Figma and implemented as a fully working web application
- Built complete trip planning features including itinerary management, booking flow, and responsive design
- Developed design system with consistent color schemes, typography, and interactive prototypes
- Developed full-stack weather application with real-time API data integration for accurate forecasting
- Built RESTful APIs with Express.js backend and responsive React frontend with state management