I’m Serhii, a senior engineer with 15+ years in frontend, several as a lead. I turn a vague request into a scope engineers can review, then build it across UI and API. Your team estimates real work instead of guessing from mockups.
I own the work through testing, release and production debugging, with a multi-agent workflow doing the legwork.
Open to employment or B2B contract
Remote · Ukraine, EET (UTC+2/+3), overlap with EU and US East
Working principles
Research before scope
I study the domain, the legacy behavior and the code before I propose scope.
Small steps that ship
I cut work into the smallest end-to-end flows that are testable and useful on their own, and release them one at a time. No big-bang launches.
Check the whole flow
I trace the complete flow myself and confirm what I find with whoever owns the code. I don’t take a colleague’s assurance or an agent’s report on trust.
Case studies
Evaluation against customer test data
A US regional bank needed to score models against its own test data, and DataRobot offered that only in a legacy UI. I owned my team’s part of moving the supervised workflow into the new product. It shipped in about five months, and within two months of GA it was in production use in banking, chemicals and manufacturing.
Customer-defined evaluation metrics
Customers could define their own evaluation metrics only through the API. I led the three-phase product integration: a UI for packages of up to 50 metrics, validation of each file as it’s uploaded, and the Python API changes behind both. All three phases were built behind a feature flag; one UI fix was still in review when I left DataRobot.
Multi-agent engineering workflow
I built it for my own work at DataRobot. Agents research, implement and test in isolated worktrees, up to four tracks at once. I set the scope, review every diff and accept the result.
Hiring for a product engineering role?
Send me the role and a few lines about the team.