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Software Engineer with 1+ years in Node.js, AI Integration & Cloud Deployment
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Assessing your cultural and operational fit
Software Engineer with hands-on experience designing and shipping production REST APIs, AI-integrated services, and cloud-native applications on AWS and DigitalOcean. Specialized in Node.js, NestJS, and Strapi, with proven delivery of OpenAI, Stripe, and Twilio integrations across mobile and web platforms. Strong foundation in LLM integration, multi-tenant architecture, and end-to-end cloud deployment.
National University of Computer and Emerging Sciences (FAST NUCES)
Bachelor of Science · Software Engineering
August 1, 2020 – June 30, 2024
Smart Coders
Backend Developer
November 1, 2024 – Present
Pakistan
Smart Coders
Backend Developer Intern
September 1, 2024 – October 1, 2024
Pakistan
Code Scrub AI Code Smell Detector
January 1, 2024 – January 1, 2024
• Built an AI-powered static analysis tool using LLMs to detect code smells across Java and JavaScript repositories, with OAuth integration to GitHub, Bitbucket, and GitLab. • Used Python and FastAPI for LLM integrations into web application. • Developed a MERN web application that orchestrates LLM inference pipelines, generates structured analysis reports, and surfaces actionable refactoring recommendations to developers. • Deployed the full-stack platform on AWS for scalable, end-to-end automated repository analysis.
iDrive e2 - White-Label Cloud Storage Platform
January 1, 2024 – January 1, 2024
• Architected a multi-tenant cloud storage backend in Node.js/Express that dynamically provisions per-user isolated S3 buckets via the iDrive e2 Reseller API at signup. • Implemented full user lifecycle: JWT authentication, profile management, pre-signed URL file upload/download/view (15-min and 1-hr expiry), and cascading account deletion with bucket cleanup. • Shipped a documented 12-endpoint API on AWS EC2 with PM2, bcrypt, SQLite, and rate limiting.
Iraqi Bazaar - Marketplace CRM
January 1, 2024 – January 1, 2024
• Developed backend services in Node.js + Strapi, integrating OpenAI voice-to-text, Stripe payments, and Twilio SMS/OTP, deployed end-to-end on AWS. • Built complete authentication flows: sign-up, login, OTP verification, and password reset.
FocusOn - Productivity App Backend
January 1, 2024 – January 1, 2024
• Built and extended backend APIs for an iOS/Android productivity app using NestJS and TypeScript, delivering issue analysis, solution-bank management, and category hierarchies secured with JWT. • Deployed on DigitalOcean with zero regression incidents across existing app workflows post-delivery.
Cricket Score Predictor - Full-Stack ML Pipeline
January 1, 2024 – January 1, 2024
• Built a full-stack score predictor using the MERN stack and Python with end-to-end MLOps: DVC/Airflow for dataset versioning, MLflow for experiment tracking, and Docker Minikube deployment via GitHub Actions.
AWS Academy Graduate Microservices and CI/CD Pipeline Builder
Amazon Web Services
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project portfolio demonstrates a strong interest in modern technologies like Generative AI, MLOps, and cloud computing, which aligns well with innovative and forward-thinking engineering cultures. The diversity of projects (ML pipelines, cloud storage, marketplace CRM, AI code analysis) indicates a broad technical curiosity and ability to work across different domains. Their experience with Agile/Scrum tools (Jira) suggests familiarity with common development methodologies. The AWS certification further reinforces a commitment to professional development and cloud best practices. The candidate's experience with both personal and academic projects, alongside professional roles, shows initiative and a continuous learning mindset.
Soft Skills & Operational Fit
The candidate's resume indicates a proactive approach to learning and development, as evidenced by their rapid promotion from intern to full-time developer. Their project descriptions suggest an ability to work on diverse technical challenges and deliver end-to-end solutions. The focus on 'zero major post-release incidents' and 'zero regression incidents' points to a detail-oriented and quality-conscious mindset. The variety of projects, from cloud storage to AI code smell detection, suggests adaptability and a willingness to tackle complex problems. However, without direct assessment data on communication or teamwork, these aspects are inferred from project descriptions.