Awais is a Python developer and software engineer at Algotix AI who builds automation systems, web scrapers, browser automation and backend services — practical software that keeps running after you stop looking at it.
I build thoughtful software for the real world
Products, platforms and systems thoughtfully built to be simple, reliable and ready to scale.
A software engineer with a practical mindset.
Currently working as a Software Engineer at
That curiosity grew into a love for building things across the stack. From backend systems and APIs to web and mobile experiences, I enjoy understanding how the pieces fit together and turning an idea into something real.
I like starting with the problem, keeping the solution clear and building with purpose. Whether I am working on a product, a service or the systems behind it, I care about software that feels simple to use, works reliably and can grow with the people using it.
For me, good engineering is not about how much you can build. It is about how thoughtfully you build it.
Just over a year of professional engineering, built on tools I made for myself first.
1 Sep 2025 — Currently working
At Algotix AI, I work across backend, web and mobile development to build software for real-world use.
From APIs and services to automation, data pipelines and integrations, I turn complex requirements into reliable systems and products.
I work through the full development process, continuously refining what I build to make it more robust, maintainable and ready for production.
Python underneath all of it, and the tools around it that I work with most. Drag the field to move through them.
One platform. Thirty scrapers. Every morning.
A Django platform that runs more than thirty job-board scrapers from a single, database-driven configuration. Each source has its own adapter; a CLI runs them one at a time or as the daily batch. Results land in organised Google Sheets tabs, and the system notifies when a source changes shape.
Supplier workflows that notice when they break.
Browser automation for industrial MRO supplier and marketplace workflows: placing orders, collecting confirmations, following tracking. A monitoring layer watches prices and availability, catches failed orders, and repairs broken automation flows before a person has to.
Analytics for many channels, on autopilot.
A Google Apps Script system that authenticates several YouTube channels through OAuth 2.0, pulls analytics on a schedule and writes structured reports into Google Sheets. It replaced a weekly manual export with a workflow nobody has to remember.
A production FastAPI backend in one command.
An open-source command-line tool published to PyPI. Choose a database, ORM, Docker, tests, linting, CI and a Makefile; FastForgeX generates a complete, fully typed FastAPI project that runs without a single edit. Interactive, flag and preset modes cover both first-timers and scripts.
A hundred thousand questions, served calmly.
A large educational platform for exam preparation: forty-seven subjects, fifty exam tracks, more than a hundred thousand questions and hundreds of study links. The browser never touches the database — a serverless API layer holds every key, validates input, rate-limits and paginates.
Knowledge for AI agents, with receipts.
A grounding layer for AI agents. Every source — URL, PDF, video or image — is normalised into one schema and stored locally in SQLite and LanceDB with a resolvable anchor, a publication date and a quality score. When the model is wrong, one click shows exactly why. Exposed as an MCP server and a CLI.
About work, tools, or an automation problem worth solving. I read everything.