Open to opportunities

Systems Engineer · Platform Builder

I make AI-driven engineering
predictable at scale

From first engineer to leading a product used by thousands daily.Now building the infrastructure layer that makes agents ship code — not just suggest it.

Proof of Work

Not promises. Results.

HR-tech startup → Kaspersky acquisition

Problem

Early-stage product with no engineering team, no architecture, no processes.

Solution

Joined as first engineer. Built the team, established architecture, led Vue 2→3 migration without stopping delivery.

Result

Product scaled to thousands of daily users across major enterprise clients. Releases went from stressful events to routine deploys.

KB Labs — solo-built platform

Problem

AI agents generate code, but nobody controls how. No observability, no policy enforcement, no reproducibility.

Solution

Designed and built a 125-package platform: plugin system, workflow engine, semantic search, agent orchestration.

Result

Full engineering automation stack — self-hosted, policy-first, built by one engineer. OSS core shipping today.

Scaling engineering processes

Problem

Manual code reviews bottleneck delivery. Quality depends on who reviews, not on what's reviewed.

Solution

Built AI review pipeline with heuristic + LLM layers, baseline ratcheting, regression detection.

Result

Automated quality gates that catch regressions before merge. Review quality became consistent and measurable.

About

Builder, not a commentator

Most teams talk about AI-assisted development. I built the platform. 125 packages, 18 monorepos, agents that actually ship code — not just autocomplete it.

First engineer at a Kaspersky subsidiary → team lead → architectural owner. Now I sit at round tables with C-level discussing how to make agent-driven engineering predictable at scale — and then go home and build it.

We switched to tractors, but the field stayed the same size. I'm working on the field.

Technologies I work with

TypeScriptNode.jsVueReactNext.jsGoFastifyDockerRedisQdrantOpenAIAnthropicGitHub ActionsVitestPlaywrightVitepnpmTurborepoTypeScriptNode.jsVueReactNext.jsGoFastifyDockerRedisQdrantOpenAIAnthropicGitHub ActionsVitestPlaywrightVitepnpmTurborepo

Experience

Where I've been building

2025 - Presentcurrent

KB Labs

Founder

Open-source platform for engineering automation. Plugin system, workflow engine, semantic search, agent orchestration — OSS core with commercial layer ahead.

  • 125 packages, 18 monorepos — designed, built, and shipping solo
  • On-prem deployment in one command, policy-first workflows out of the box
  • OSS core today, enterprise capabilities on the roadmap
2021 - 2025

Forpeople (Kaspersky)

Engineering Lead

Joined as the first frontend engineer at an early-stage HR-tech product inside Kaspersky. Grew it from startup to acquisition — used daily by thousands of employees at major enterprise clients.

  • Built team from 0 → hired, onboarded, and mentored engineers
  • Product scaled from MVP to enterprise clients with thousands of daily users
  • Led Vue 2 → 3 migration without stopping feature delivery
  • Made releases boring — from stressful events to routine deploys
2019 - 2021

Inverse Studio

Co-Founder / CTO

Co-founded a web studio. Learned that the hardest part of engineering isn't code — it's translating business needs into technical decisions under real constraints.

  • Full ownership: client → requirements → architecture → delivery → support
  • Established engineering standards that outlived my involvement
2018 - 2019

Zixinet

Frontend Developer

Where it started. Corporate sites, landing pages, learning to write code that other people have to maintain.

  • Built reusable component library — my first taste of platform thinking

Philosophy

How I think about engineering

principles.sh
>Pet projects don't scale to departments. Systems do.
>Three similar lines > one premature abstraction.
>AI without observability is just expensive chaos.
>We can produce more features now. Coordinating them — not so much.
>Boring, observable, policy-driven. Pick all three.
$ type "help" to explore

What I optimize for

Observability

If you can't see it, you can't control it

Agent Predictability

AI output you can verify and trust

Cost of Coordination

More features, same bottleneck — unless you fix it

Time to Confidence

How fast can you trust a release

Open-Source Platform

KB Labs

A plugin-first platform that replaces script chaos with managed, observable automation. OSS core you can self-host today, with commercial capabilities on the roadmap.

0

Packages

0

Monorepos

0

Engineer

“Every dependency should be replaceable without a rewrite.”