About Me

I’m an AI Solutions Architect and Consultant with over a decade of corporate experience spanning Software Engineering, Product Management, Project Ownership, and hands-on Technical Consulting. My work bridges the gap implementation and strategy—from building data pipelines and MLOps frameworks to leading cross-functional teams in global enterprises.

My Focus: Data Sovereignty & Sustainable AI

In a world awash with (sometimes overwhelmingly large) cloud platforms and hidden vendor lock-ins, I’m on a mission to ensure businesses stay in control of their data and infrastructure when building their AI systems. Whether it’s deploying AI in hybrid environments, setting up Kubernetes-based GPU clusters for large-scale ML, or architecting RAG based GenAI solutions for complex use cases—my priority is always to help clients remain agile and independent.

Why Work With Me?

Technical Depth + Business Savvy: I’m both an engineer and a strategist. I’ve managed high-stakes AI projects, driven digital transformation in industrial settings, and know how to communicate ROI to executive stakeholders.
No-Nonsense Approach: I believe in delivering real, operational solutions—not just proofs-of-concept or big talk. Expect straight answers, clear timelines, and actionable results.
Enterprise-Scale MLOps: I design and implement cloud-native, production-grade systems that ensure models can be deployed, monitored, and retrained effortlessly.
Trusted Advisor & Developer: I’m not just giving advice; I also roll up my sleeves and build. My background includes everything from IoT platforms to generative AI solutions that process tens of thousands of daily queries.

Where I Can Help

Data & AI Strategy: Clarifying the “what” and “why” of your AI roadmap, with a keen eye on maintaining data sovereignty.
Solution Architecture & MLOps: Designing high-performance, scalable AI platforms—be it on-premises, cloud, or a hybrid setup.
Cross-Functional Leadership: Leading diverse teams across engineering, operations, and business functions to ensure seamless deployment.
Future-Proofing: Implementing open, flexible systems that adapt as your needs evolve, without hidden ecosystem lock-ins.

If you’re seeking sustainable, enterprise-grade AI solutions without compromising control over your data—or if you simply want to talk shop on building robust ML infrastructures—consider to subscribing to this publication and connect with me here:

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I’m always interested in collaborating with like-minded professionals and helping businesses unlock the full potential of AI, on their own terms.