Requirements, mapped to real production experience.
I'm an SRE / Platform Architect building production platforms where reliability, scalability, observability and automation directly affect business-critical services — across financial services, iGaming, financial crime prevention, aviation and enterprise. My current work supports Anti-Fraud, AML and KYC workloads; I'm extending it into AI infrastructure and AI-assisted operations.
Comfortable in English-speaking engineering environments — written technical communication, documentation, incident discussions and async collaboration.
SRE / Platform Architect with production experience across Kubernetes, GitOps, observability, Financial Crime platforms and ML infrastructure.
Reliability layer for real-time anti-fraud platforms.
Every transaction is evaluated in real time, and every decision has to be available, observable and reliable. My role is to keep the infrastructure behind those systems resilient, scalable and continuously deployable.
I also explore AI-assisted operational tooling as an extension of SRE practices — covered in AI Direction.
I keep business-critical, real-time platforms reliable, observable and continuously deployable.
How the platform fits together — and how it's built.
I work across the full platform stack: business-critical workloads, Kubernetes-based platform capabilities, infrastructure foundations, production operations, and the AI/MLOps direction I'm extending toward.
Every platform I build follows the same delivery path — the real tools I run daily, from a developer's commit through production and back again as a feedback loop.
A platform is not a one-way pipeline. It's a loop — production signals shape the next commit as much as the commit shapes production.
Where I've built and operated production platforms.
From telecom security through Kubernetes consulting to leading DevOps functions and owning business-critical SRE platforms — each role compounds into the platform engineering I do today.
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The principles behind every platform I build.
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Architecture decisions, with the trade-offs made explicit.
Senior platform work is mostly judgment. These are real decisions from production platforms — the problem, the choice, and what it cost.
How my platforms — and I — have evolved.
Every migration below replaced something that worked with something that scaled — the pattern behind how I approach platform engineering.
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Extending SRE practice into AI-assisted operations.
I already run production MLOps infrastructure — GPU Kubernetes, training pipelines, model serving. The next step is applying AI to operations itself: tooling that investigates, explains and acts under human supervision.
AI doesn't replace SRE judgment — it extends it. Reliable automation still needs someone who understands what reliable means.