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Principal Solution Architect

Company Context

Philips is a global health-technology company focused on clinical systems, imaging, patient monitoring, and health informatics.

Summary

Principal Solution Architect at Philips, Jan 2019 to Apr 2020. Architected and deployed a scalable, AI-powered clinical platform used by 300+ hospitals globally, bridging software engineering, compliance, and AI model interoperability to enable edge inference, observability, and regulated medical device delivery.

Responsibilities

  • Designed and led implementation of a container-based AI application platform, enabling hospitals to securely deploy and manage ML inference workloads on imaging studies (CT, MRI, X-ray)
  • Spearheaded the development of a Clinical AI App Store, supporting third-party models via containerisation and common execution contracts — decoupling diagnostic logic from deployment pipelines
  • Orchestrated integrations with hospital infrastructure using HL7 and FHIR standards, creating seamless data pipelines between imaging equipment, PACS/RIS systems, and AI models
  • Created a diagnosis feedback loop by tapping into HL7 lab messaging to track downstream confirmations (e.g. cancer) — enabling real-world model validation and clinical QA
  • Applied Kubernetes operator patterns to manage application lifecycle in air-gapped, VMWare-based environments, including upgrade orchestration and fault recovery
  • Delivered high-availability clusters tailored for hospital-grade resilience; defined compute/storage SLAs and multi-node rollout procedures
  • Ensured ISO 13485 and IEC 62304 compliance through audit-ready deployment infrastructure, test traceability, and automated delivery gates
  • Coordinated global delivery teams (Germany, India, UK), aligning infrastructure, application logic, and security postures across regional requirements

Outcomes

  • Delivered an AI-powered clinical platform used by 300+ hospitals globally.
  • Enabled model portability and controlled deployment through app-store style packaging and execution contracts for third-party models.
  • Created a diagnosis feedback loop enabling real-world model validation and clinical QA.
  • Coordinated global delivery teams across Germany, India, and UK.

Reusable CV Bullets

  • Architected and deployed a scalable, AI-powered clinical platform used by 300+ hospitals globally, enabling edge inference and regulated medical device delivery
  • Spearheaded a Clinical AI App Store supporting third-party models via containerisation and common execution contracts
  • Orchestrated integrations with hospital infrastructure using HL7 and FHIR standards, connecting imaging equipment, PACS/RIS systems, and AI models
  • Created a diagnosis feedback loop via HL7 lab messaging to track downstream confirmations, enabling real-world model validation and clinical QA
  • Applied Kubernetes operator patterns to manage application lifecycle in air-gapped, VMWare-based environments, including upgrade orchestration and fault recovery
  • Delivered high-availability clusters tailored for hospital-grade resilience with defined compute/storage SLAs
  • Ensured ISO 13485 and IEC 62304 compliance through audit-ready deployment infrastructure and automated delivery gates
  • Coordinated global delivery teams (Germany, India, UK), aligning infrastructure, application logic, and security postures

Evidence / Source Notes

  • Source: config/madu_profile.json → work_experience[]; reconciled with JobVia export (madu_alikor_export.json).
  • Confidence: high