Krunal Sabnis
AI Systems Architect — Production Systems for Regulated Environments
Two decades building production systems — cloud-native platforms, distributed architectures, DevOps at scale. Now focused on AI systems that must work in real environments — where governance, privacy, and traceability are hard requirements, not afterthoughts. Based in Amsterdam.
What I do
I design and build systems that can operate reliably under real-world constraints:
- Systems architecture — cloud-native, on-premise, hybrid. Platforms that run at scale and pass compliance.
- Private AI systems — voice, data pipelines, governance. Fully on-prem, air-gapped, edge-deployable.
- Platform engineering — Kubernetes workloads, MLOps, CI/CD, observability. Systems built for global scale.
Selected systems
Where I operate
How I engage
I work on problems where:
- AI needs to run in production, not just demos
- Data privacy or compliance is a hard constraint
- System architecture matters more than framework choice
I engage where I can own architecture and outcomes, working closely with domain experts as part of a focused collaboration.
Track record
Led architecture of a SaaS platform from zero to acquisition by Copado — same codebase running cloud and on-premise at Ministry of Defence NL.
Built IoT platform featured at AWS re:Invent (Pitney Bowes).
Previously at IBM — big data platforms across banking, telecom, and enterprise SaaS.
Most AI systems fail not because of models — but because they can't operate reliably in real environments.
If you're working on something in this space, reach out.