Afaq A.

Backend Engineer

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Bio

Afaq A. is a highly skilled backend developer and data scientist with a strong academic foundation, currently pursuing a Bachelor of Science in Data Science from NUCES-FAST. He brings hands-on experience in Python, Django, AWS, AI, Git, Docker, Linux, Celery, Redis, SQL, React, JavaScript, VS Code, MySQL, and Tableau, alongside proficiency in advanced AI topics such as generative AI and NLP. At Uurnik Systems, Afaq has demonstrated success designing and maintaining RESTful APIs, building cloud automation solutions with…

  • Projects completed2
  • Hourly rate
  • 0-2 years experience
  • Member since Mar 2026
Expertise
PythonGitSQLReactAWSSeleniumJavascriptWebScraping
Video Intro
Assessments

General Project Assessment

Great on Implement LRU Cache Algorithm, Difficulty Medium · Great on Understanding Rate Limiting in APIs, Difficulty Medium · Great on Ensuring Real-time Data Accuracy in Mobile App, Difficulty Medium

Projects

ScholarWatch

Collaborated in a team of 3 to build an AI-enhanced Moodle plugin with 7+ features; including gaze tracking, quiz generation, and weak-area analysis, providing smart engagement tools and personalized learning insights for remote education. Implemented RAG using LangChain's vectorStoreIndex with Gemini 2.5 LLM for generating personalized dynamic quizzes with 90%+ accuracy in topic alignment. Built an analytics dashboard for students and instructors, delivering personalized academic insights, weak-area detection, engagement metrics, and performance trends through real-time visualization of learning data. Utilized Git for version control to manage codebase collaboration and ensure structured development workflows.

Research: Multimodal Deepfake Detection using ViT, PPG & Cross-Attention

Co-authored a research paper, proposing a novel deepfake detection framework combining Vision Transformers (ViT) for facial analysis and Photoplethysmography (PPG) for physiological signal extraction. Integrated a cross-attention mechanism to align visual and pulse-based cues for improved detection accuracy. Achieved 82.6% accuracy on a subset of Celeb-DF-v2 (890 real, 890 fake videos), showcasing strong results with limited resources. Contributed to model design, dataset preparation, and co-writing of the research paper.

Experience

  1. Backend Developer

    Uurnik SystemsOct 2024 — Present
    • Collaborating in an Agile development environment to deliver software solutions.
    • Designing, developing and maintaining 20+ RESTful APIs and endpoints using Django for scalable backend services.
    • Developed an agentic RAG chatbot with a custom-built Model Context Protocol (MCP) server using Langgraph, automating ~70% of routine workflows and enabling dynamic task execution through conversational interfaces.
    • Built backend support for cloud automation using AWS (Customer Gateways, Virtual Gateways, Site-to-Site VPNs) via the Boto3 SDK, improving deployment reliability and security.
    • Implemented asynchronous task execution using Celery, offloading heavy computations and external API calls to background workers, reducing request latency significantly.
    • Developed and managed Celery Beat scheduled tasks for recurring jobs, improving system automation and reducing manual operational effort.
    • Implemented network automation for multi-vendor routers (Cisco, Juniper, Fortinet), enhancing efficiency and reducing manual configuration efforts time by ~60%.
    • Utilized Git for version control, contributing to 30+ commits/month in collaborative development.
    PythonDjangoAWSAIGitDockerLinuxCeleryRedis

  2. Lab Demonstrator

    NUCES-FASTFeb 2024 — May 2024
    • Guided 60+ undergraduate students across 2 core courses (Databases and Computer Organization & Assembly Language).
    • Resolved 50+ student queries, improving student lab performance by ~20% through concept clarification and live debugging.
    SQLAssembly

  3. Data Science Intern

    Graana.comJun 2023 — Aug 2023
    • Scraped and processed 1000+ property listings using BeautifulSoup and Selenium for structured data extraction.
    • Automated OCR pipeline using Tesseract, increasing document data extraction speed by 40%.
    • Leveraged NLP methods to preprocess text and hypertune T5-small for English to Urdu translation.
    Python
Education

  1. Bachelor of Science (Data Science)

    National University of Computer & Emerging Sciences (NUCES-FAST)Islamabad, Pakistan2021 — 2025
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