The work
- Building the product From discovery onwards: understanding the problem and the outcome before deciding how to build it, ideally before the scope is locked, then new systems or extensions of existing ones, through to production. Education SaaS
- Applied AI R&D On the workflows a team uses every day: researching where they can get better, prototyping, and saying honestly whether AI fits, in the process or in the product. Often that means several AIs working through one main agent that knows my standards: it writes each tool's input and checks what comes back. Product AI is newer ground for me, and I want to learn it. Claude Design playbook: repo ·memo
- DevEx / AI-native SDLC Building how a team delivers with AI agents in the real workflow: the gates, conventions and tooling that make AI-written code safe to ship, so the whole team gets the same results, not just one person. Pipeforge: project ·memo
The team
- I have a real say in the technical approach.
- Testing and production quality belong to the people who build.
- Knowledge flows both ways: I share what I've learned and learn from the others.
- There's room to improve how the team works, not only what it ships.
- Product questions reach someone who can answer them.
Location
An office in or near Rzeszów, or fully remote.