Engineering Leadership at the Crossroads of AI, Systems & Product

I build and operate AI and software systems under real constraints.

My work sits at the intersection of engineering leadership, product strategy, and operational reality. I build systems that survive scale, ambiguity, and real-world constraints — and I build teams that can evolve them.

CTO / Head of Engineering Profile

01. How My Career Evolved

Phase I — Technical Breadth

→Early engineering roles in distributed systems, DevOps, Backend, and Mobile.
→Learning how systems fail in production.
→Building foundational technical intuition across the stack.

Phase II — Organizational Systems

→Tradelab: Engineering governance & regulatory systems.
→Managing infrastructure leadership, GDPR compliance, and SSO unification.
→Formal management, hiring, and cross-team alignment.

Phase III — Full-System Ownership

→WonderStream → Showdown: Full-spectrum AI systems & Studio leadership.
→Operating financial monitoring & trading systems under risk.
→Merging executive strategy with incident ownership & cost control.

02. Leadership Timeline

2020 — Now

CTO — Showdown Lab

Full-spectrum AI systems + studio leadership. Building financial & operational automation.

2018 — 2020

Team Lead — Tradelab

Infrastructure & Cloud Services. Engineering governance & regulatory systems (GDPR).

2016 — 2018

CTO — WonderStream

Real-time data infrastructure under pressure. Live broadcast analytics.

2012 — 2016

Engineering Foundations

Mobile, DevOps, Backend, Distributed Systems.

Showdown Lab

AI Systems Under Real Constraints

PARIS, FRANCE · 2020 — PRESENT

Python

Golang

JavaScript

NodeJS

HTML

CSS

React

Next.JS

Vue.JS

Vite

Bootstrap

Tailwind

DaisyUI

ShadCN

Pandas

Generative AI

Vision AI

AI Pipelines

GCP

Docker

Infrastructure

Financial Trading

NinjaScript

PineScript

R&D / Strategy

Management

Negotiation

Context

Studio building and operating AI-driven systems for clients and internal products across finance, applied AI, and operational automation.

Scope

Strategy & Product Direction
Led engineering team (up to ~10 engineers)
Managed hiring & performance reviews
Client pre-sales & investor discussions

Leadership

Hybrid Executive + Technical execution
Incident ownership & reliability
Cost-aware AI architecture
Engineering under uncertainty

What I Built & Operated

Pocket Moni

LLM-based WhatsApp AI access layer. Architected pluggable AI infrastructures with model interchangeability.

AiFred

Multi-stage audio-to-structured-intelligence system. Managed API volatility and production instability.

Rubel App

AI-assisted scheduling for luxury operations. Formalized operational constraints before automation.

Golden Chaos

Real-time financial data ingestion and analysis. Managed unreliable external APIs and data freshness.

What Was at Risk

Financial accuracy
Real-time data freshness
AI API volatility
Operational scheduling corruption

Tradelab

Engineering Governance at Scale

PARIS, FRANCE · 2018 — 2020

Python

JavaScript

Node.js

HTML

CSS

Angular

Pandas

Jupyter

GCP

Docker

GDPR

Management

Context

Global digital advertising company operating under strict data, compliance, and operational constraints.

Scope

Team Lead — Infra & Cloud Services
Peak ~7 engineers (direct), ~20 indirect scope
Hiring, performance reviews, budget definition
Reported to Head of Engineering & HR

Leadership

Engineering Governance
Risk-aware system design
Cross-team conflict resolution
Technical alignment

Core Impact & Systems

GDPR Compliance Infrastructure

Led technical design of secure data deletion and audit systems on large historical datasets. Coordinated engineering, product, legal, and executive stakeholders.

Company-wide SSO ("Gandalf")

Unified identity management to reduce fragmentation across technical stacks. Strengthened collaboration between infrastructure and product teams.

What Was at Risk

Regulatory fines
Data deletion failure
Operational shutdown risk
Reputation damage

WonderStream

Real-Time Data Under Pressure

PRAGUE, CZECH REPUBLIC · 2016 — 2018

Python

Node.js

JavaScript

Pandas

AWS

Kafka

Kinesis

Docker

Management

Cassandra

Redis

Context

Data analytics company focused on live broadcast and eSports metrics. I served as the final technical authority alongside the CEO.

Scope

Chief Technology Officer
Led engineering team (peak ~4 engineers)
Full infrastructure authority
Integration of data science into production

System Pressure

~1M events/day processing
Latency-sensitive live pipelines
Cloud cost control under volatility
Unpredictable traffic spikes

Key Engineering

Distributed ETL Pipelines

Built with Kafka, Kinesis, SQS, Redis, Cassandra. Ensured uptime and latency stability during live events.

Behavioral Analysis (Pre-LLM)

Designed ML-driven systems. Tuned models in production under real-world noisy data.

Engineering Foundations

Before stepping into executive leadership, I built my technical intuition through hands-on roles in Backend, DevOps, Mobile, and Distributed Systems research.