About

The short version: I fix the parts of your business that should already be automatic

Hi, I am Shahvaiz Ahmed. I have spent the last seven years as a data engineer and AI automation specialist, and somewhere in there I picked up a slightly obsessive habit of looking at any repetitive task and immediately thinking "this should not require a human."

That habit has turned into a career built around exactly one thing: making businesses run smoother by removing the manual steps that nobody actually wants to be doing.

How I got here

I started in data engineering, working with systems that genuinely could not afford to fail. At OMERS, one of Canada's largest pension funds, I built and maintained ETL pipelines pulling live financial data from Bloomberg, MSCI, and SQL systems into a centralized data warehouse. I built dashboards that portfolio managers actually used. I led a full migration of our orchestration layer from Apache Airflow to Prefect without disrupting a single day of operations.

That experience taught me something that stuck: in high-stakes environments, "it mostly works" is not good enough. Systems need to be built assuming things will go wrong, because eventually they do.

From there, I moved into AI and automation work, because the same principles apply whether you are processing financial data or qualifying sales leads. At PSL Group, I built an LLM-powered research tool for medical teams, deployed on AWS, that cut document review time from a full day to a few minutes. For marketing agencies and SaaS businesses, I have built AI-driven lead qualification systems, automated outreach engines, and intelligent request-routing tools that handle work a human used to do by hand, every single day, without complaint.

What I actually believe about this work

Automation is not about replacing people. It is about giving people their time back so they can do the work that actually needs a human brain. Every system I build is designed around that idea: handle the repetitive 80 percent automatically, and make sure the 20 percent that genuinely needs judgment gets flagged clearly for the right person.

I also believe documentation and reliability matter more than clever code. A brilliant automation that nobody on your team understands, and that breaks silently, is worse than a simple one that is well documented and alerts you the moment something goes wrong. I build for the second kind every time.

Outside the technical stuff

I work with businesses across financial services, healthcare, marketing, and e-commerce, which means I have seen the same underlying problems show up in completely different industries wearing different costumes. A pension fund's data reconciliation issue and a marketing agency's lead routing chaos are, structurally, the same problem. That cross-industry pattern recognition is honestly one of the most useful things I bring to a new project.

Want to know if your specific situation fits this kind of fix? Reach out and tell me what's going on. I will give you a straight answer, not a sales pitch.