python engineering at findev
Python work at Findev can look very different from project to project. It might mean building backend services and APIs, or automation scripts, internal tools, data processing, integrations, and CI/CD pipelines. Sometimes it is about helping with notebooks, prototypes, research tools, AI-assisted workflows, or performance issues in existing code.
A lot of our Python work starts with an idea that already exists somewhere: in a notebook, a script, a PoC, an MVP, or even in a piece of AI-generated code that works, but is not ready to become part of a real system. That is where we help. We turn useful ideas into software that can be maintained, tested, deployed, monitored, scaled, and supported. In other words, we help move Python solutions from "it works on my machine" to something the business can actually rely on.
Many of the people we work with are not professional software engineers. They are portfolio managers, quantitative analysts, risk managers, traders, and operations teams who use technology to make decisions, manage money, trade, analyze risk, or automate their daily work. They often know Python well enough to test an idea, analyze data, build a model, or automate a painful manual process. But software engineering is not their main job.
So our role is not just to write Python. We need to understand what they are trying to achieve, ask the right questions, improve the design, optimize the code, integrate it with other systems, and turn the result into something sustainable.
The range of Python work at Findev is broad:
- writing automation scripts and internal tools;
- building backends, prototypes, and new services with FastAPI, Streamlit, AWS EKS, Lambda, Fargate, RDS, Kafka, Snowflake, JupyterHub, and other tools;
- building and maintaining CI/CD pipelines;
- supporting the DevOps side of Python projects;
- developing integrations with internal and external systems;
- working on data analytics, AI, quantitative research, and R&D;
- optimizing code, refactoring old solutions, and cleaning up AI-generated "vibe code";
- troubleshooting production issues, sometimes genuinely interesting, sometimes "interesting" in the painful sense;
- supporting the wider Python ecosystem across Findev.
Here you can see the impact of your work clearly. When everything works, people simply get on with their jobs. But when something breaks, portfolio managers, quants, and researchers stop being able to do their jobs. The calls, messages, and Slack pings start immediately. That is when it becomes clear how much depends on what you have built.