I am a Software Engineer specializing in backend systems, full-stack web applications, and applied machine learning/AI. My focus is on building resilient, high-integrity software where architectural details matter, from schema design and deterministic scoring algorithms to idempotent payment workflows and automated MLOps pipelines.
- π Education: Graduated 3rd in Batch with a 3.81 CGPA in B.E. Software Engineering from Mehran University of Engineering and Technology (MUET).
- πΌ Industry Experience:
- Effective Risk Management (Remote Β· Australia): Building enterprise risk intelligence products, deterministic scoring engines with bounded LLM classification, resumable SEC EDGAR data pipelines, and full-stack marketplaces.
- 10Pearls (Remote Β· Pakistan): Developed end-to-end 72-hour air quality forecasting pipelines with MLOps automation and model explainability.
- Buildables (Remote Β· Pakistan): Engineered RAG-grounded prompt optimization platforms and voice-to-voice AI assistants.
- TIERS Limited & BitsPro: Built full-stack web platforms and REST APIs using Django, Go, and React.
- π Current Goal: Open to high-impact Backend or Full-Stack Software Engineering roles.
| Languages |
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| Backend & APIs |
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| Frontend & Mobile |
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| Databases & Storage |
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| AI & Machine Learning |
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| DevOps, Testing & Security |
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| Project | Description & Key Engineering Decisions | Tech Stack & Links |
|---|---|---|
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Practicable Enterprise Learning & Commerce Platform |
β’ Architected a 42-table PostgreSQL schema with 42 Alembic migrations across content, assessment, commerce, and audit domains. β’ Implemented 157 REST endpoints, Stripe webhook-based idempotent fulfillment, role-based access control (RBAC), and immutable audit logs. β’ Enforced a single entitlement gate deciding access across all paths. β’ Comprehensive test suite with 582 Pytest tests across 45 modules and Playwright E2E suites. |
FastAPI PostgreSQL SQLAlchemy 2.0 Alembic Stripe React 19 TypeScript Pytestπ» GitHub |
|
Pearls AQI Predictor 72-Hour Air Quality Forecasting System |
β’ Engineered a 45-feature representation strictly free of look-ahead bias with cyclical encodings and ACF/PACF-selected lag structures. β’ Benchmarked 5 ML architectures under TimeSeriesSplit CV; LightGBM achieved RΒ² = 0.98 and RMSE = 3.24.β’ Designed a 3-tier storage abstraction (MongoDB Atlas primary, Hopsworks secondary, local fallback) and GridFS-backed model registry. β’ Automated hourly ingestion and daily retraining with GitHub Actions and SHAP explainability. |
Python FastAPI LightGBM XGBoost TensorFlow MongoDB Hopsworks Streamlitπ» GitHub Β· π Live Demo |
|
FocusAid Adaptive Productivity App for ADHD |
β’ Built a deterministic 4-factor prioritization engine mapping moods, urgency, and effort without letting AI bias task ordering. β’ Fine-tuned LLaMA 3, Gemma, and Phi-2 with LoRA on PyTorch for task decomposition with structured fallback parsing. β’ Shipped 33 REST endpoints over a 7-table schema with JWT refresh-token flows and a 20-screen mobile app with gamified progression. |
FastAPI React Native (Expo) PyTorch LoRA PostgreSQL Redux Toolkitπ» GitHub |
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PromptTune RAG-Grounded Prompt Optimization Platform |
β’ Built a retrieval-augmented meta-prompting platform using a 384-dim Pinecone serverless index over an indexed prompt engineering corpus. β’ Implemented deterministic parsing of tag-delimited outputs into prompt, rationale, and evaluation checklists. β’ Features persona management, session state retention, and full CRUD REST APIs. |
Python FastAPI Pinecone LangChain Groq (Llama 3.3) React PostgreSQLπ» GitHub |
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Affordable Meals UN SDG 1 & 2 Nutrition & Budget Planner |
β’ Built a 17-endpoint Express REST API with 20 versioned SQL migrations across 15 PostgreSQL tables. β’ Deterministic carbon-footprint scoring engine based on emission factors with graceful LLM fallback failover (OpenRouter β Groq β local data). β’ Developed full community feed, ratings, and social Open Graph preview generation. |
Express 5 Node.js PostgreSQL Drizzle ORM React 19 TypeScript Tailwindπ» GitHub Β· π Live Demo |
I'm always excited to discuss software engineering, distributed backend systems, and applied AI opportunities.

