System Architect-AI platform

Job Summary

As the Hardware Architect for Philips Multi-Modal Imaging AI General Management Platform, you will lead end-to-end hardware architecture design for our unified edge and on-prem AI platform. This platform runs on SUSE Linux Micro + K3s, supporting containerized AI workloads (TensorRT/ONNX/NVIDIA acceleration) and virtualized SaMD applications via KubeVirt/KVM. You will collaborate closely with software architects, clinical product teams, regulatory QA, and global engineering to define hardware specifications for multi-modal medical devices including CT, MR, DSA, and Ultrasound. You will balance clinical performance, medical regulatory compliance, air-gapped hospital deployment constraints, power and thermal limits, and long-term platform scalability to support cardiovascular, neuro, stroke, pulmonary, and structural heart AI workflows.

Key Responsibilities

1. Develop and maintain the overall hardware reference architecture for the multi-modal medical imaging AI platform, covering edge on-device deployments integrated with DSA/CT/MR/ultrasound and hospital on-prem server clusters.

2. Co-design with software architects to align hardware capabilities with K3s, KubeVirt virtualization, GPU acceleration, distributed monitoring (OpenTelemetry), air-gapped software packaging (Zarf), and secure remote access (FRP). Optimize resource partitioning between containerized AI workloads and VM-based SaMD workloads.

3. Define compute, GPU, memory, storage, and network specifications for medical-grade hardware; conduct vendor evaluation, benchmarking, and performance validation for NVIDIA accelerators, local high-speed storage, and low-latency IO for medical DICOM image streams.

4. Address medical environment constraints including air-gapped deployment, EMI/EMC requirements, thermal management, 24/7 clinical continuous operation, and hospital power resilience.

5. Support medical regulatory alignment with NMPA, IEC 62304, and IEC 60601. Collaborate with QA and regulatory teams to document hardware architecture, risk analysis, and hardware change control for SaMD and AI medical applications.

6. Lead hardware performance benchmarking for multi-modality image reconstruction, AI inference latency, and concurrent workload testing for clinical AI pipelines such as FFR, surgical planning, and lesion assessment.

7. Evaluate hardware supply chain options, define reference BOMs, and design the hardware upgrade roadmap for the 2026-2028 platform rollout timeline covering DSA/CT pilot, EI product expansion, and mass clinical rollout.

8. Collaborate with global Philips hardware teams and local clinical customers to collect site requirements and resolve deployment hardware issues during prototype validation and clinical pilot phases.

9. Create hardware architecture documentation, reference design whitepapers, and architecture review materials for internal technical reviews and executive presentations.

Required Qualifications & Experience

1. Bachelor's or Master's degree in Computer Engineering, Electronic Engineering, Hardware Systems, or related disciplines.

2. 5+ years of professional experience as a hardware architect or senior hardware system engineer, with proven experience designing server or edge computing hardware for on-prem or edge AI workloads.

3. Deep knowledge of x86 hardware architecture, PCIe, GPU architecture (NVIDIA preferred), high-speed storage (NVMe), and low-latency networking. Hands-on experience with virtualization (KVM) and containerized workload hardware resource planning.

4. Practical understanding of Linux-based systems (SUSE Linux preferred). Familiarity with hardware resource allocation for mixed workloads, including virtual machine workloads alongside GPU-accelerated container AI workloads.

5. Experience conducting system-level performance benchmarking, thermal and power budget analysis, and hardware sizing for parallel inference workloads.

6. Working knowledge of IT infrastructure requirements in hospital environments; experience with air-gapped, secure medical system deployment is a strong plus.

7. Fluent written and spoken English, capable of communicating with global cross-functional teams.

Preferred Qualifications

1. Previous working experience in the medical device or medical imaging industry. Experience with CT, MR, DSA, or ultrasound systems is highly preferred.

2. Awareness of medical device standards including IEC 60601, IEC 62304, and NMPA medical software and SaMD compliance requirements.

3. Familiarity with Kubernetes/K3s, KubeVirt, and GPU virtualization resource scheduling concepts such as vGPU and Mdev.

4. Experience designing hybrid edge-server hardware architectures supporting DICOM multi-modal imaging pipelines.

5. Experience in hardware specification definition for long-lifecycle industrial or medical platforms with 7-10 year support cycles.

What We Offer

• Opportunity to architect a flagship unified AI platform for Philips multi-modality clinical imaging products.

• Cross-border collaboration with global Philips medical technology teams.

• Clear roadmap spanning prototype development, clinical pilot, and nationwide market rollout.

• Competitive compensation, flexible working policies, complete medical industry training, and regulatory development resources.